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How to Write Quantitative Research Questions: Types With Examples

How to Write Quantitative Research Questions: Types With Examples

For research to be effective, it becomes crucial to properly formulate the quantitative research questions in a correct way. Otherwise, you will not get the answers you were looking for.

Has it ever happened that you conducted a quantitative research study and found out the results you were expecting are quite different from the actual results?

This could happen due to many factors like the unpredictable nature of respondents, errors in calculation, research bias, etc. However, your quantitative research usually does not provide reliable results when questions are not written correctly.

We get it! Structuring the quantitative research questions can be a difficult task.

Hence, in this blog, we will share a few bits of advice on how to write good quantitative research questions. We will also look at different types of quantitative research questions along with their examples.

Let’s start:

How to Write Quantitative Research Questions?

When you want to obtain actionable insight into the trends and patterns of the research topic to make sense of it, quantitative research questions are your best bet.

Being objective in nature, these questions provide you with detailed information about the research topic and help in collecting quantifiable data that can be easily analyzed. This data can be generalized to the entire population and help make data-driven and sound decisions.

Respondents find it easier to answer quantitative survey questions than qualitative questions . At the same time, researchers can also analyze them quickly using various statistical models.

However, when it comes to writing the quantitative research questions, one can get a little overwhelmed as the entire study depends on the types of questions used.

There is no “one good way” to prepare these questions. However, to design well-structured quantitative research questions, you can follow the 4-steps approach given below:

1. Select the Type of Quantitative Question

The first step is to determine which type of quantitative question you want to add to your study. There are three types of quantitative questions:

  • Descriptive
  • Comparative 
  • Relationship-based

This will help you choose the correct words and phrases while constructing the question. At the same time, it will also assist readers in understanding the question correctly.

2. Identify the Type of Variable

The second step involves identifying the type of variable you are trying to measure, manipulate, or control. Basically, there are two types of variables:

  • Independent variable (a variable that is being manipulated)
  • Dependent variable (outcome variable)

quantitative questions examples

If you plan to use descriptive research questions, you have to deal with a number of dependent variables. However, where you plan to create comparative or relationship research questions, you will deal with both dependent and independent variables.

3. Select the Suitable Structure

The next step is determining the structure of the research question. It involves:

  • Identifying the components of the question. It involves the type of dependent or independent variable and a group of interest (the group from which the researcher tries to conclude the population).
  • The number of different components used. Like, as to how many variables and groups are being examined.
  • Order in which these are presented. For example, the independent variable before the dependent variable or vice versa.

4. Draft the Complete Research Question

The last step involves identifying the problem or issue that you are trying to address in the form of complete quantitative survey questions. Also, make sure to build an exhaustive list of response options to make sure your respondents select the correct response. If you miss adding important answer options, then the ones chosen by respondents may not be entirely true.

Types of Quantitative Research Questions With Examples

Quantitative research questions are generally used to answer the “who” and “what” of the research topic. For quantitative research to be effective, it is crucial that the respondents are able to answer your questions concisely and precisely. With that in mind, let’s look in greater detail at the three types of formats you can use when preparing quantitative market research questions.

1. Descriptive

Descriptive research questions are used to collect participants’ opinions about the variable that you want to quantify. It is the most effortless way to measure the particular variable (single or multiple variables) you are interested in on a large scale. Usually, descriptive research questions begin with “ how much,” “how often,” “what percentage,” “what proportion,” etc.

Examples of descriptive research questions include:

2. Comparative

Comparative research questions help you identify the difference between two or more groups based on one or more variables. In general, a comparative research question is used to quantify one variable; however, you can use two or more variables depending on your market research objectives.

Comparative research questions examples include:

3. Relationship-based

Relationship research questions are used to identify trends, causal relationships, or associations between two or more variables. It is not vital to distinguish between causal relationships, trends, or associations while using these types of questions. These questions begin with “What is the relationship” between independent and dependent variables, amongst or between two or more groups.

Relationship-based quantitative questions examples include:

Ready to Write Your Quantitative Research Questions?

So, there you have it. It was all about quantitative research question types and their examples. By now, you must have figured out a way to write quantitative research questions for your survey to collect actionable customer feedback.

Now, the only thing you need is a good survey maker tool, like ProProfs Survey Maker, that will glide your process of designing and conducting your surveys . You also get access to various survey question types, both qualitative and quantitative, that you can add to any kind of survey along with professionally-designed survey templates .

Jared Cornell

About the author

Jared cornell.

Jared is a customer support expert. He has been published in CrazyEgg , Foundr , and CXL . As a customer support executive at ProProfs, he has been instrumental in developing a complete customer support system that more than doubled customer satisfaction. You can connect and engage with Jared on Twitter , Facebook , and LinkedIn .

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What Are Quantitative Survey Questions? Types and Examples

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Table of contents: 

  • Types of quantitative survey questions - with examples 
  • Quantitative question formats
  • How to write quantitative survey questions 
  • Examples of quantitative survey questions 

Leveraging quantilope for your quantitative survey 

In a quantitative research study brands will gather numeric data for most of their questions through formats like numerical scale questions or ranking questions. However, brands can also include some non-quantitative questions throughout their quantitative study - like open-ended questions, where respondents will type in their own feedback to a question prompt. Even so, open-ended answers can be numerically coded to sift through feedback easily (e.g. anyone who writes in 'Pepsi' in a soda study would be assigned the number '1', to look at Pepsi feedback as a whole).  One of the biggest benefits of using a quantitative research approach is that insights around a research topic can undergo statistical analysis; the same can’t be said for qualitative data like focus group feedback or interviews. Another major difference between quantitative and qualitative research methods is that quantitative surveys require respondents to choose from a limited number of choices in a close-ended question - generating clear, actionable takeaways. However, these distinct quantitative takeaways often pair well with freeform qualitative responses - making quant and qual a great team to use together.  The rest of this article focuses on quantitative research, taking a closer look at quantitative survey question types and question formats/layouts. 

Back to table of contents 

Types of dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139745">quantitative survey questions - with examples 

Quantitative questions come in many forms, each with different benefits depending on dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139784">your dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139740">market research objectives. Below we’ll explore some of these dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139745">quantitative dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139785">survey question dropdown#toggle" data-dropdown-menu-id-param="menu_term_281139785" data-dropdown-placement-param="top" data-term-id="281139785"> types, which are commonly used together in a single survey to keep things interesting for dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents . The style of questioning used during dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139739">quantitative dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139750">data dropdown#toggle" data-dropdown-menu-id-param="menu_term_281139750" data-dropdown-placement-param="top" data-term-id="281139750"> collection is important, as a good mix of the right types of questions will deliver rich data, limit dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondent fatigue, and optimize the dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139757">response rate . dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139742">Questionnaires should be enjoyable - and varying the dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139755">types of dropdown#toggle" data-dropdown-menu-id-param="menu_term_281139755" data-dropdown-placement-param="top" data-term-id="281139755">quantitative research dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139755"> questions used throughout your survey will help achieve that. 

Descriptive survey questions

dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139763">Descriptive research questions (also known as usage and attitude, or, U&A questions) seek a general indication or prediction about how a dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139773">group of people behaves or will behave, how that group is characterized, or how a group thinks.

For example, a business might want to know what portion of adult men shave, and how often they do so. To find this out, they will survey men (the dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139743">target audience ) and ask descriptive questions about their frequency of shaving (e.g. daily, a few times a week, once per week, and so on.) Each of these frequencies get assigned a numerical ‘code’ so that it’s simple to chart and analyze the data later on; daily might be assigned ‘5’, a few times a week might be assigned ‘4’, and so on. That way, brands can create charts using the ‘top two’ and ‘bottom two’ values in a descriptive question to view these metrics side by side.

Another business might want to know how important local transit issues are to residents, so dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139745">quantitative survey questions will allow dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents to indicate the degrees of opinion attached to various transit issues. Perhaps the transit business running this survey would use a sliding numeric scale to see how important a particular issue is.

Comparative survey questions

dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139782">Comparative research questions are concerned with comparing individuals or groups of people based on one or more variables. These questions might be posed when a business wants to find out which segment of its dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139743">target audience might be more profitable, or which types of products might appeal to different sets of consumers.

For example, a business might want to know how the popularity of its chocolate bars is spread out across its entire customer base (i.e. do women prefer a certain flavor? Are children drawn to candy bars by certain packaging attributes? etc.). Questions in this case will be designed to profile and ‘compare’ segments of the market.

Other businesses might be looking to compare coffee consumption among older and younger consumers (i.e. dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139741">demographic segments), the difference in smartphone usage between younger men and women, or how women from different regions differ in their approach to skincare.

Relationship-based survey questions

As the name suggests, relationship-based survey questions are concerned with the relationship between two or more variables within one or more dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139741">demographic groups. This might be a dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139759">causal link between one thing and the other - for example, the consumption of caffeine and dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents ’ reported energy levels throughout the day. In this case, a coffee or energy drink brand might be interested in how energy levels differ between those who drink their caffeinated line of beverages and those who drink decaf/non-caffeinated beverages.

Alternatively, it might be a case of two or more factors co-existing, without there necessarily being a dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139759">causal link - for example, a particular type of air freshener being more popular amongst a certain dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139741">demographic (maybe one that is controlled wirelessly via Bluetooth is more popular among younger homeowners than one that’s plugged into the wall with no controls). Knowing that millennials favor air fresheners which have options for swapping out scents and setting up schedules would be valuable information for new product development.

Advanced method survey questions

Aside from descriptive, comparative, and relationship-based survey questions, brands can opt to include advanced methodologies in their quantitative dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139742">questionnaire for richer depth. Though advanced methods are more complex in terms of the insights output, quantilope’s Consumer Intelligence Platform automates the setup and analysis of these methods so that researchers of any background or skillset can leverage them with ease.

With quantilope’s pre-programmed suite of 12 advanced methodologies , including MaxDiff , TURF , Implicit , and more, users can drag and drop any of these into a dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139742">questionnaire and customize for their own dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139740">market research objectives.

For example, consider a beverage company that’s looking to expand its flavor profiles. This brand would benefit from a MaxDiff which forces dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents to make tradeoff decisions between a set of flavors. A dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondent might say that coconut is their most-preferred flavor, and lime their least (when in a consideration set with strawberry), yet later on in the MaxDiff that same dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondent may say Strawberry is their most-preferred flavor (over black cherry and kiwi). While this is just one example of an advanced method, instantly you can see how much richer and more actionable these quantitative metrics become compared to a standard usage and attitude question .

Advanced methods can be used alongside descriptive, comparison, or relationship questions to add a new layer of context wherever a business sees fit. Back to table of contents 

Quantitative question formats  

So we’ve covered the kinds of dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139736">quantitative research questions you might want to answer using dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139740">market research , but how do these translate into the actual format of questions that you might include on your dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139742">questionnaire ?

Thinking ahead to your reporting process during your dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139742">questionnaire setup is actually quite important, as the available chart types differ among the types of questions asked; some question data is compatible with bar chart displays, others pie charts, others in trended line graphs, etc. Also consider how well the questions you’re asking will translate onto different devices that your dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents might be using to complete the survey (mobile, PC, or tablet).

Single Select questions

Single select questions are the simplest form of quantitative questioning, as dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents are asked to choose just one answer from a list of items, which tend to be ‘either/or’, ‘yes/no’, or ‘true/false’ questions. These questions are useful when you need to get a clear answer without any qualifying nuances.

yesno

Multi-select questions

Multi-select questions (aka, dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139767">multiple choice ) offer more flexibility for responses, allowing for a number of responses on a single question. dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">Respondents can be asked to ‘check all that apply’ or a cap can be applied (e.g. ‘select up to 3 choices’).

For example:

multiselect

Aside from asking text-based questions like the above examples, a brand could also use a single or multi-select question to ask respondents to select the image they prefer more (like different iterations of a logo design, packaging options, branding colors, etc.). 

dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139749">Likert dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139766">scale dropdown#toggle" data-dropdown-menu-id-param="menu_term_281139766" data-dropdown-placement-param="top" data-term-id="281139766"> questions

A dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139749">Likert scale   is widely used as a convenient and easy-to-interpret rating method. dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">Respondents find it easy to indicate their degree of feelings by selecting the response they most identify with.

likertscale

Slider scales

Slider scales are another good interactive way of formatting questions. They allow dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents to customize their level of feeling about a question, with a bit more variance and nuance allowed than a numeric scale:

logo slider scale example

One particularly common use of a slider scale in a dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139740">market dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139770">research dropdown#toggle" data-dropdown-menu-id-param="menu_term_281139770" data-dropdown-placement-param="top" data-term-id="281139770"> study is known as a NPS (Net Promoter Score) - a way to measure dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139775">customer experience and loyalty . A 0-10 scale is used to ask customers how likely they are to recommend a brand’s product or services to others. The NPS score is calculated by subtracting the percentage of ‘detractors’ (those who respond with a 0-6) from the percentage of promoters (those who respond with a 9-10). dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">Respondents who select 7-8 are known as ‘passives’.

For example: 

nps

Drag and drop questions

Drag-and-drop question formats are a more ‘gamified’ approach to survey capture as they ask dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents to do more than simply check boxes or slide a scale. Drag-and-drop question formats are great for ranking exercises - asking dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents to place answer options in a certain order by dragging with their mouse. For example, you could ask survey takers to put pizza toppings in order of preference by dragging options from a list of possible answers to a box displaying their personal preferences:

ranking poster

Matrix questions

Matrix   questions are a great way to consolidate a number of questions that ask for the same type of response (e.g. single select yes/no, true/false, or multi-select lists). They are mutually beneficial - making a survey look less daunting for the dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondent , and easier for a brand to set up than asking multiple separate questions.

Items in a matrix question are presented one by one, as respondents cycle through the pages selecting one answer for each coffee flavor shown. 

Untitled design (5)-1

While the above example shows a single-matrix question - meaning a respondent can only select one answer per element (in this case, coffee flavors), a matrix setup can also be used for multiple-choice questions - allowing respondents to choose multiple answers per element shown, or for rating questions - allowing respondents to assign a rating (e.g. 1-5) for a list of elements at once.  Back to table of contents 

How to write dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139745">quantitative survey questions  

We’ve reviewed the types of questions you might ask in a quantitative survey, and how you might format those questions, but now for the actual crafting of the content.

When considering which questions to include in your survey, you’ll first want to establish what your research goals are and how these relate to your business goals. For example, thinking about the three types of dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139745">quantitative survey questions explained above - descriptive, comparative, and relationship-based - which type (or which combination) will best meet your research needs? The questions you ask dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents may be phrased in similar ways no matter what kind of layout you leverage, but you should have a good idea of how you’ll want to analyze the results as that will make it much easier to correctly set up your survey.

Quantitative questions tend to start with words like ‘how much,’ ‘how often,’ ‘to what degree,’ ‘what do you think of,’ ‘which of the following’ - anything that establishes what consumers do or think and that can be assigned a numerical code or value. Be sure to also include ‘other’ or ‘none of the above’ options in your quant questions, accommodating those who don’t feel the pre-set answers reflect their true opinion. As mentioned earlier, you can always include a small number of dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139748">open-ended questions in your quant survey to account for any ideas or expanded feedback that the pre-coded questions don’t (or can’t) cover. Back to table of contents 

Examples of dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139745">quantitative survey questions  

dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139745">Quantitative survey questions impose limits on the answers that dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents can choose from, and this is a good thing when it comes to measuring consumer opinions on a large scale and comparing across dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents . A large volume of freeform, open-ended answers is interesting when looking for themes from qualitative studies, but impractical to wade through when dealing with a large dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139756">sample size , and impossible to subject to dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139774">statistical analysis .

For example, a quantitative survey might aim to establish consumers' smartphone habits. This could include their frequency of buying a new smartphone, the considerations that drive purchase, which features they use their phone for, and how much they like their smartphone.

Some examples of quantitative survey questions relating to these habits would be:

Q. How often do you buy a new smartphone?

[single select question]

More than once per year

Every 1-2 years

Every 3-5 years

Every 6+ years

Q. Thinking about when you buy a smartphone, please rank the following factors in order of importance:

[drag and drop ranking question]

screen size

storage capacity

Q. How often do you use the following features on your smartphone?

[matrix question]

Q. How do you feel about your current smartphone?

[sliding scale]

I love it <-------> I hate it

Answers from these above questions, and others within the survey, would be analyzed to paint a picture of smartphone usage and attitude trends across a population and its sub-groups. dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139738">Qualitative research might then be carried out to explore those findings further - for example, people’s detailed attitudes towards their smartphones, how they feel about the amount of time they spend on it, and how features could be improved. Back to table of contents 

quantilope’s Consumer Intelligence Platform specializes in automated, advanced survey insights so that researchers of any skill level can benefit from quick, high-quality consumer insights. With 12 advanced methods to choose from and a wide variety of quantitative question formats, quantilope is your one-stop-shop for all things dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139740">market research (including its dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139776">in-depth dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139738">qualitative research solution - inColor ).

When it comes to building your survey, you decide how you want to go about it. You can start with a blank slate and drop questions into your survey from a pre-programmed list, or you can get a head start with a survey dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139765">template for a particular business use case (like concept testing ) and customize from there. Once your survey is ready to launch, simply specify your dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139743">target audience , connect any panel (quantilope is panel agnostic), and watch as dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139783">answer questions in your survey in real-time by monitoring the fieldwork section of your project. AI-driven dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139764">data analysis takes the raw data and converts it into actionable findings so you never have to worry about manual calculations or statistical testing.

Whether you want to run your quantitative study entirely on your own or with the help of a classically trained research team member, the choice is yours on quantilope’s platform. For more information on how quantilope can help with your next dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139736">quantitative dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139768">research dropdown#toggle" data-dropdown-menu-id-param="menu_term_281139768" data-dropdown-placement-param="top" data-term-id="281139768"> project , get in touch below!

Get in touch to learn more about quantitative research with quantilope!

Related posts, your guide to better brand health tracking, better brand health tracking: what's the 'takeout' soda brand, better brand health tracking series: mental advantage analysis, how to use ai for automated data analysis and visualization.

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A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.

INTRODUCTION

Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

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Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

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EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

  • EXAMPLE 1. Descriptive research question (quantitative research)
  • - Presents research variables to be assessed (distinct phenotypes and subphenotypes)
  • “BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
  • RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
  • EXAMPLE 2. Relationship research question (quantitative research)
  • - Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
  • “Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
  • Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
  • EXAMPLE 3. Comparative research question (quantitative research)
  • - Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
  • “BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
  • RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
  • STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
  • EXAMPLE 4. Exploratory research question (qualitative research)
  • - Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
  • “Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
  • EXAMPLE 5. Relationship research question (quantitative research)
  • - Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
  • “Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

  • EXAMPLE 1. Working hypothesis (quantitative research)
  • - A hypothesis that is initially accepted for further research to produce a feasible theory
  • “As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
  • “In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
  • EXAMPLE 2. Exploratory hypothesis (qualitative research)
  • - Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
  • “We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
  • “Conclusion
  • Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
  • EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
  • “We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
  • Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
  • EXAMPLE 4. Statistical hypothesis (quantitative research)
  • - An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
  • “Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
  • “Statistical Analysis
  • ( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27

EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS

  • EXAMPLE 1. Background, hypotheses, and aims are provided
  • “Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
  • “ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
  • “This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
  • EXAMPLE 2. Background, hypotheses, and aims are provided
  • “We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
  • “ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
  • EXAMPLE 3. Background, aim, and hypothesis are provided
  • “In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
  • “This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
  • “ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

  • Conceptualization: Barroga E, Matanguihan GJ.
  • Methodology: Barroga E, Matanguihan GJ.
  • Writing - original draft: Barroga E, Matanguihan GJ.
  • Writing - review & editing: Barroga E, Matanguihan GJ.

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Research Questions Tutorial

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What is a Quantitative Research Question?

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A research question is the driving question(s) behind your research. It should be about an issue that you are genuinely curious and/or passionate about. A good research question is:

Clear :  The purpose of the study should be clear to the reader, without additional explanation.

Focused :  The question is specific. Narrow enough in scope that it can be thoroughly explored within the page limits of the research paper. It brings the common thread that weaves throughout the paper.

Concise :  Clarity should be obtained in the fewest possible words. This is not the place to add unnecessary descriptors and fluff (i.e. “very”).

Complex :  A true research question is not a yes/no question. It brings together a collection of ideas obtained from extensive research, without losing focus or clarity.

Arguable :  It doesn’t provide a definitive answer. Rather, it presents a potential position that future studies could debate.

The format of a research question will depend on a number of factors, including the area of discipline, the proposed research design, and the anticipated analysis.

Unclear:   Does loneliness cause the jitters? Clear:   What is the relationship between feelings of loneliness, as measured by the Lonely Inventory, and uncontrollable shaking?

Unfocused:   What’s the best way to learn? Focused:   In what ways do different teaching styles affect recall and retention in middle schoolers?

Verbose :  Can reading different books of varying genres influence a person’s performance on a test that measures familiarity and knowledge of different words?

Concise:   How does exposure to words through reading novels influence a person’s language development?

Definitive:   What is my favorite color? Arguable:   What is the most popular color amongst teens in America?

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98 Quantitative Research Questions & Examples

98 Quantitative Research Questions & Examples

As researchers, we know how powerful quantitative research data can be in helping answer strategic questions. Here, I’ve detailed 23 use cases and curated 98 quantitative market research questions with examples – making this a post you should add to your bookmark list 📚, so you can quickly refer back.

I’ve formatted this post to show you 10-15 questions for each use case. At the end of each section, I also share a quicker way to get similar insights using modern market research tools like Similarweb.

What is a quantitative research question?

Quantitative market research questions tell you the what, how, when, and where of a subject. From trendspotting to identifying patterns or establishing averages– using quantitative data is a clear and effective way to start solving business problems.

Types of quantitative research questions

Quantitative market research questions are divided into two main types: descriptive and causal.

  • Descriptive research questions seek to quantify a phenomenon by focusing on a certain population or phenomenon to measure certain aspects of it, such as frequency, average, or relationship.
  • Causal research questions explore the cause-and-effect relationship between two or more variables.

The ultimate list of questions for quantitative market research

Get clear explanations of the different applications and approaches to quantitative research–with the added bonus of seeing what questions to ask and how they can impact your business.

Examples of quantitative research questions for competitive analysis

A powerful example of quantitative research in play is when it’s used to inform a competitive analysis . A process that’s used to analyze and understand how industry leaders and companies of interest are performing.

Pro Tip: Collect data systematically, and use a competitive analysis framework to record your findings. You can refer back to it when you repeat the process later in the year.

  • What is the market share of our major competitors?
  • What is the average purchase price of our competitors’ products?
  • How often do our competitors release new products?
  • What is the total number of customer reviews for our competitors’ products?
  • What is the average rating of our competitors’ products?
  • What is the average customer satisfaction score for our competitors?
  • What is the average return rate of our competitors’ products?
  • What is the average shipping time for our competitors’ products?
  • What is the average price discount offered by our competitors?
  • What is the average lifespan of our competitors’ products?

With this data, you can determine your position in the market and benchmark your performance against rival companies. It can then be used to improve offerings, service standards, pricing, positioning, and operational effectiveness. Notice that all questions can be answered with a numerical response , a key component of all successful examples of quantitative market research questions.

Quantitative research question example: market analysis

🙋‍♀️ Question: What is the market share of our major competitors?

🤓 Insight sought: Industry market share of leaders and key competitors.

🤯 Challenges with traditional quantitative research methods: Outdated data is a major consideration; data freshness remains critical, yet is often tricky to obtain using traditional research methods. Markets shift fast, so being able to obtain and track market share in real time is a challenge many face.

💡 A new approach: Similarweb enables you to track this key business KPI in real-time using digital data directly from the platform. On any day, you can see what your market share is, along with any players in your market. Plus, you get to see rising stars showing significant growth, who may pose a threat through market disruption or new tactics.

⏰ Time to insight: 30 seconds

✅ How it’s done: Using Similarweb’s Web Industry Analysis, two digital metrics give you the intel needed to decipher the market share in any industry. I’m using the Banking, Credit, and Lending market throughout these examples. I’ve selected the US market, analyzing the performance of the previous 3 months.

  • Share of visits 

quantitative market research example

Here, I can see the top players in my market based on the number of unique visitors to their sites. On top of the raw data that shows me the volume of visitors as a figure, I can quickly see the two players ( Capital One and Chase ) that have grown and by what percentage. On the side, you can see rising players in the industry. Now, while my initial question was to establish the market share of my major competitors, I can see there are a few disruptive players in my market who I’d want to track too; Synchrony.com being one of particular interest, given their substantial growth and traffic numbers.

  • Share of search 

quantitative market research question example

Viewing the overall market size based on total search volumes, you can explore industry leaders in more detail. The top websites are the top five players, ranking by traffic share . You can also view the month-over-month change in visits, which shows you who is performing best at any given time . It’s the same five names, with Paypal and Chase leading the pack. However, I see Wells Fargo is better at attracting repeat visitors, while Capital One and Bank of America perform better at drawing in unique visitors.

In answer to my question, what is the market share of my major competitors, I can quickly use Similarweb’s quantitative data to get my answer.

Traffic distribution breakdown with Similarweb

This traffic share visual can be downloaded from the platform. It plots the ten industry leader’s market share and allocates the remaining share to the rest of the market.

industry leader’s market share quadrant

I can also download a market quadrant analysis, which takes two key data points, traffic share and unique visitors, and plots the industry leaders. All supporting raw data can be downloaded in .xls format or connected to other business intelligence platforms via the API.

Quantitative research questions for consumer behavior studies

These studies measure and analyze consumer behavior, preferences, and habits . Any type of audience analysis helps companies better understand customer intent, and adjust offerings, messaging, campaigns, SEO, and ultimately offer more relevant products and services within a market.

  • What is the average amount consumers spend on a certain product each month?
  • What percentage of consumers are likely to purchase a product based on its price?
  • How do the demographics of the target audience affect their purchasing behavior?
  • What type of incentive is most likely to increase the likelihood of purchase?
  • How does the store’s location impact product sales and turnover?
  • What are the key drivers of product loyalty among consumers?
  • What are the most commonly cited reasons for not buying a product?
  • How does the availability of product information impact purchasing decisions?
  • What is the average time consumers spend researching a product before buying it?
  • How often do consumers use social media when making a purchase decision?

While applying a qualitative approach to such studies is also possible, it’s a great example of quantitative market research in action. For larger corporations, studies that involve a large, relevant sample size of a target market deliver vital consumer insights at scale .

Read More: 83 Qualitative Research Questions & Examples

Quantitative research question and answer: content strategy and analysis

🙋‍♀️ Question: What type of content performed best in the market this past month?

🤓 Insight sought: Establish high-performing campaigns and promotions in a market.

🤯 Challenges with traditional quantitative research methods: Whether you consider putting together a panel yourself, or paying a company to do it for you, quantitative research at scale is costly and time-consuming. What’s more, you have to ensure that sampling is done right and represents your target audience.

💡 A new approach: Data analysis is the foundation of our entire business. For over 10 years, Similarweb has developed a unique, multi-dimensional approach to understanding the digital world. To see the specific campaigns that resonate most with a target audience, use Similarweb’s Popular Pages feature. Key metrics show which campaigns achieve the best results for any site (including rival firms), campaign take-up, and periodic changes in performance and interest.

✅ How it’s done: I’ve chosen Capital One and Wells Fargo to review. Using the Popular Pages campaign filter, I can view all pages identified by a URL parameter UTM. For clarity, I’ve highlighted specific campaigns showing high-growth and increasing popularity. I can view any site’s trending, new, or best-performing pages using a different filter.

popular pages extract Similarweb

In this example, I have highlighted three campaigns showing healthy growth, covering teen checking accounts, performance savings accounts, and add-cash-in-store. Next, I will perform the same check for another key competitor in my market.

Wells Fargo popular pages extract Similarweb

Here, I can see financial health tools campaigns with over 300% month-over-month growth and smarter credit and FICO campaigns showing strong performance. This tells me that campaigns focussing on education and tools are growing in popularity within this market. 

Examples of quantitative research questions for brand tracking

These studies are designed to measure customers’ awareness, perceptions, behaviors, and attitudes toward a brand over time. Different applications include measuring brand awareness , brand equity, customer satisfaction, and purchase or usage intent.

quantitative research questions for brand tracking

These types of research surveys ask questions about brand knowledge, brand attributes, brand perceptions, and brand loyalty . The data collected can then be used to understand the current state of a brand’s performance, identify improvements, and track the success of marketing initiatives.

  • To what extent is Brand Z associated with innovation?
  • How do consumers rate the quality of Brand Z’s products and services?
  • How has the awareness of Brand Z changed over the past 6 months?
  • How does Brand Z compare to its competitors in terms of customer satisfaction?
  • To what extent do consumers trust Brand Z?
  • How likely are consumers to recommend Brand Z?
  • What factors influence consumers’ purchase decisions when considering Brand Z?
  • What is the average customer satisfaction score for equity?
  • How does equity’s customer service compare to its competitors?
  • How do customer perceptions of equity’s brand values compare to its competitors?

Quantitative research question example and answer: brand tracking

🙋‍♀️ Question: How has the awareness of Brand Z changed over the past 6 months?

🤓 Insight sought: How has brand awareness changed for my business and competitors over time.

⏰ Time to insight: 2 minutes

✅ How it’s done: Using Similarweb’s search overview , I can quickly identify which brands in my chosen market have the highest brand awareness over any time period or location. I can view these stats as a custom market or examine brands individually.

Quantitative research questions example for brand awareness

Here, I’ve chosen a custom view that shows me five companies side-by-side. In the top right-hand corner, under branded traffic, you get a quick snapshot of the share of website visits that were generated by branded keywords. A branded keyword is when a consumer types the brand name + a search term.

Below that, you will see the search traffic and engagement section. Here, I’ve filtered the results to show me branded traffic as a percentage of total traffic. Similarweb shows me how branded search volumes grow or decline monthly. Helping me answer the question of how brand awareness has changed over time.

Quantitative research questions for consumer ad testing

Another example of using quantitative research to impact change and improve results is ad testing. It measures the effectiveness of different advertising campaigns. It’s often known as A/B testing , where different visuals, content, calls-to-action, and design elements are experimented with to see which works best. It can show the impact of different ads on engagement and conversions.

A range of quantitative market research questions can be asked and analyzed to determine the optimal approach.

  • How does changing the ad’s headline affect the number of people who click on the ad?
  • How does varying the ad’s design affect its click-through rate?
  • How does altering the ad’s call-to-action affect the number of conversions?
  • How does adjusting the ad’s color scheme influence the number of people who view the ad?
  • How does manipulating the ad’s text length affect the average amount of time a user spends on the landing page?
  • How does changing the ad’s placement on the page affect the amount of money spent on the ad?
  • How does varying the ad’s targeting parameters affect the number of impressions?
  • How does altering the ad’s call-to-action language impact the click-through rate?

Quantitative question examples for social media monitoring

Quantitative market research can be applied to measure and analyze the impact of social media on a brand’s awareness, engagement, and reputation . By tracking key metrics such as the number of followers, impressions, and shares, brands can:

  • Assess the success of their social media campaigns
  • Understand what content resonates with customers
  • Spot potential areas for improvement
  • How often are people talking about our brand on social media channels?
  • How many times has our brand been mentioned in the past month?
  • What are the most popular topics related to our brand on social media?
  • What is the sentiment associated with our brand across social media channels?
  • How do our competitors compare in terms of social media presence?
  • What is the average response time for customer inquiries on social media?
  • What percentage of followers are actively engaging with our brand?
  • What are the most popular hashtags associated with our brand?
  • What types of content generate the most engagement on social media?
  • How does our brand compare to our competitors in terms of reach and engagement on social media?

Example of quantitative research question and answer: social media monitoring

🙋‍♀️ Question: How does our brand compare to our competitors in terms of reach and engagement on social media?

🤓 Insight sought: The social channels that most effectively drive traffic and engagement in my market

✅ How it’s done: Similarweb Digital Research Intelligence shows you a marketing channels overview at both an industry and market level. With it, you can view the most effective social media channels in any industry and drill down to compare social performance across a custom group of competitors or an individual company.

Here, I’ve taken the five closest rivals in my market and clicked to expand social media channel data. Wells Fargo and Bank of America have generated the highest traffic volume from social media, with over 6.6 million referrals this year. Next, I can see the exact percentage of traffic generated by each channel and its relative share of traffic for each competitor. This shows me the most effective channels are Youtube, Facebook, LinkedIn, and Reddit – in that order.

Quantitative social media questions

In 30-seconds, I’ve discovered the following:

  • YouTube is the most popular social network in my market.
  • Facebook and LinkedIn are the second and third most popular channels.
  • Wells Fargo is my primary target for a more in-depth review, with the highest performance on the top two channels.
  • Bank of America is outperforming all key players significantly on LinkedIn.
  • American Express has found a high referral opportunity on Reddit that others have been unable to match.

Power-up Your Market Research with Similarweb Today

Examples of quantitative research questions for online polls.

This is one of the oldest known uses of quantitative market research. It dates back to the 19th century when they were first used in America to try and predict the outcome of the presidential elections.

quantitative research questions for online polls

Polls are just short versions of surveys but provide a point-in-time perspective across a large group of people. You can add a poll to your website as a widget, to an email, or if you’ve got a budget to spend, you might use a company like YouGov to add questions to one of their online polls and distribute it to an audience en-masse.

  • What is your annual income?
  • In what age group do you fall?
  • On average, how much do you spend on our products per month?
  • How likely are you to recommend our products to others?
  • How satisfied are you with our customer service?
  • How likely are you to purchase our products in the future?
  • On a scale of 1 to 10, how important is price when it comes to buying our products?
  • How likely are you to use our products in the next six months?
  • What other brands of products do you purchase?
  • How would you rate our products compared to our competitors?

Quantitative research questions for eye tracking studies

These research studies measure how people look and respond to different websites or ad elements. It’s traditionally an example of quantitative research used by enterprise firms but is becoming more common in the SMB space due to easier access to such technologies.

  • How much time do participants spend looking at each visual element of the product or ad?
  • How does the order of presentation affect the impact of time spent looking at each visual element?
  • How does the size of the visual elements affect the amount of time spent looking at them?
  • What is the average time participants spend looking at the product or ad as a whole?
  • What is the average number of fixations participants make when looking at the product or ad?
  • Are there any visual elements that participants consistently ignore?
  • How does the product’s design or advertising affect the average number of fixations?
  • How do different types of participants (age, gender, etc.) interact with the product or ad differently?
  • Is there a correlation between the amount of time spent looking at the product or ad and the participants’ purchase decision?
  • How does the user’s experience with similar products or ads affect the amount of time spent looking at the current product or ad?

Quantitative question examples for customer segmentation

Segmentation is becoming more important as organizations large and small seek to offer more personalized experiences. Effective segmentation helps businesses understand their customer’s needs–which can result in more targeted marketing, increased conversions, higher levels of loyalty, and better brand awareness.

quantitative research questions for segmentation

If you’re just starting to segment your market, and want to know the best quantitative research questions to ask to help you do this, here are 20 to choose from.

Examples of quantitative research questions to segment customers

  • What is your age range?
  • What is your annual household income?
  • What is your preferred online shopping method?
  • What is your occupation?
  • What types of products do you typically purchase?
  • Are you a frequent shopper?
  • How often do you purchase products online?
  • What is your typical budget for online purchases?
  • What is your primary motivation for purchasing products online?
  • What factors influence your decision to purchase a product online?
  • What device do you use most often when shopping online?
  • What type of product categories are you most interested in?
  • Do you prefer to shop online for convenience or for a better price?
  • What type of discounts or promotions do you look for when making online purchases?
  • How do you prefer to receive notifications about product promotions or discounts?
  • What type of payment methods do you prefer when shopping online?
  • What methods do you use to compare different products and prices when shopping online?
  • What type of customer service do you expect when shopping online?
  • What type of product reviews do you consider when making online purchases?
  • How do you prefer to interact with a brand when shopping online?

Examples of quantitative research questions for analyzing customer segments

  • What is the average age of customers in each segment?
  • How do spending habits vary across customer segments?
  • What is the average length of time customers spend in each segment?
  • How does loyalty vary across customer segments?
  • What is the average purchase size in each segment?
  • What is the average frequency of purchases in each segment?
  • What is the average customer lifetime value in each segment?
  • How does customer satisfaction vary across customer segments?
  • What is the average response rate to campaigns in each segment?
  • How does customer engagement vary across customer segments?

These questions are ideal to ask once you’ve already defined your segments. We’ve written a useful post that covers the ins and outs of what market segmentation is and how to do it.

Additional applications of quantitative research questions

I’ve covered ten use cases for quantitative questions in detail. Still, there are other instances where you can put quantitative research to good use.

Product usage studies: Measure how customers use a product or service.

Preference testing: Testing of customer preferences for different products or services.

Sales analysis: Analysis of sales data to identify trends and patterns.

Distribution analysis: Analyzing distribution channels to determine the most efficient and effective way to reach customers.

Focus groups: Groups of consumers brought together to discuss and provide feedback on a particular product, service, or marketing campaign.

Consumer interviews: Conducted with customers to understand their behavior and preferences better.

Mystery shopping: Mystery shoppers are sent to stores to measure customer service levels and product availability.

Conjoint analysis: Analysis of how consumers value different attributes of a product or service.

Regression analysis: Statistical analysis used to identify relationships between different variables.

A/B testing: Testing two or more different versions of a product or service to determine which one performs better.

Brand equity studies: Measure, compare and analyze brand recognition, loyalty, and consumer perception.

Exit surveys: Collect numerical data to analyze employee experience and reasons for leaving, providing insight into how to improve the work environment and retain employees.

Price sensitivity testing: Measuring responses to different pricing models to find the optimal pricing model, and identify areas if and where discounts or incentives might be beneficial.

Quantitative market research survey examples

A recent GreenBook study shows that 89% of people in the market research industry use online surveys frequently–and for good reason. They’re quick and easy to set up, the cost is minimal, and they’re highly scalable too.

Quantitative market research method examples

Questions are always formatted to provide close-ended answers that can be quantified. If you wish to collect free-text responses, this ventures into the realm of qualitative research . Here are a few examples.

Brand Loyalty Surveys: Companies use online surveys to measure customers’ loyalty to their brand. They include questions about how long an individual has been a customer, their overall satisfaction with the service or product, and the likelihood of them recommending the brand to others.

Customer Satisfaction Surveys: These surveys may include questions about the customer’s experience, their overall satisfaction, and the likelihood they will recommend a product or service to others.

Pricing Studies: This type of research reveals how customers value their products or services. These surveys may include questions about the customer’s willingness to pay for the product, the customer’s perception of the price and value, and their comparison of the price to other similar items.

Product/Service Usage Studies: These surveys measure how customers use their products or services. They can include questions about how often customers use a product, their preferred features, and overall satisfaction.

Here’s an example of a typical survey we’ve used when testing out potential features with groups of clients. After they’ve had the chance to use the feature for a period, we send a short survey, then use the feedback to determine the viability of the feature for future release.

Employee Experience Surveys: Another great example of quantitative data in action, and one we use at Similarweb to measure employee satisfaction. Many online platforms are available to help you conduct them; here, we use Culture AMP . The ability to manipulate the data, spot patterns or trends, then identify the core successes and development areas are astounding.

Qualitative customer experience example Culture AMP

Read a connected post that shows 18 ways to use market research surveys .

How to answer quantitative research questions with Similarweb

For the vast majority of applications I’ve covered in this post, there’s a more modern, quicker, and more efficient way to obtain similar insights online. Gone are the days when companies need to use expensive outdated data or pay hefty sums of money to market research firms to conduct broad studies to get the answers they need.

By this point, I hope you’ve seen how quick and easy it is to use Similarweb to do market research the modern way. But I’ve only scratched the surface of its capabilities.

Take two to watch this introductory video and see what else you can uncover.

Added bonus: Similarweb API

If you need to crunch large volumes of data and already use tools like Tableau or PowerBI, you can seamlessly connect Similarweb via the API and pipe in the data. So for faster analysis of big data, you can leverage Similarweb data to use alongside the visualization tools you already know and love.

Similarweb’s suite of market intelligence solutions offers unbiased, accurate, honest insights you can trust. With a world of data at your fingertips, use Similarweb Digital Research Intelligence to uncover telling facts that help inform your research and strengthen your position.

Use it for:

Market Research

Benchmarking

Audience Insights

Company Research

Consumer Journey Tracking

Wrapping up

Today’s markets change at lightning speed. To keep up and succeed, companies need access to insights and intel they can depend on to be timely and on-point. While quantitative market research questions can and should always be asked, it’s important to leverage technology to increase your speed to insight, and thus improve reaction times and response to market shifts.

What is quantitative market research?

Quantitative market research is a form of research that uses numerical data to gain insights into the behavior and preferences of customers. It is used to measure and track the performance of products, services, and campaigns.

How does quantitative market research help businesses?

Quantitative market research can help businesses identify customer trends, measure customer satisfaction, and develop effective marketing strategies. It can also provide valuable insights into customer behavior, preferences, and attitudes.

What types of questions should be included in a quantitative market research survey?

Questions in a quantitative market research survey should be focused, clear, and specific. Questions should be structured to collect quantitative data, such as numbers, percentages, or frequency of responses.

What methods can be used to collect quantitative market research data?

Common methods used to collect quantitative market research data include surveys, interviews, focus groups, polls, and online questionnaires.

What are the advantages and disadvantages of using quantitative market research?

The advantages of using quantitative market research include the ability to collect data quickly, the ability to analyze data in a structured way, and the ability to identify trends. Disadvantages include the potential for bias, the cost of collecting data, and the difficulty in interpreting results.

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How to structure quantitative research questions

There is no "one best way" to structure a quantitative research question. However, to create a well-structured quantitative research question, we recommend an approach that is based on four steps : (1) Choosing the type of quantitative research question you are trying to create (i.e., descriptive, comparative or relationship-based); (2) Identifying the different types of variables you are trying to measure, manipulate and/or control, as well as any groups you may be interested in; (3) Selecting the appropriate structure for the chosen type of quantitative research question, based on the variables and/or groups involved; and (4) Writing out the problem or issues you are trying to address in the form of a complete research question. In this article, we discuss each of these four steps , as well as providing examples for the three types of quantitative research question you may want to create: descriptive , comparative and relationship-based research questions .

  • STEP ONE: Choose the type of quantitative research question (i.e., descriptive, comparative or relationship) you are trying to create
  • STEP TWO: Identify the different types of variable you are trying to measure, manipulate and/or control, as well as any groups you may be interested in
  • STEP THREE: Select the appropriate structure for the chosen type of quantitative research question, based on the variables and/or groups involved
  • STEP FOUR: Write out the problem or issues you are trying to address in the form of a complete research question

STEP ONE Choose the type of quantitative research question (i.e., descriptive, comparative or relationship) you are trying to create

The type of quantitative research question that you use in your dissertation (i.e., descriptive , comparative and/or relationship-based ) needs to be reflected in the way that you write out the research question; that is, the word choice and phrasing that you use when constructing a research question tells the reader whether it is a descriptive, comparative or relationship-based research question. Therefore, in order to know how to structure your quantitative research question, you need to start by selecting the type of quantitative research question you are trying to create: descriptive, comparative and/or relationship-based.

STEP TWO Identify the different types of variable you are trying to measure, manipulate and/or control, as well as any groups you may be interested in

Whether you are trying to create a descriptive, comparative or relationship-based research question, you will need to identify the different types of variable that you are trying to measure , manipulate and/or control . If you are unfamiliar with the different types of variable that may be part of your study, the article, Types of variable , should get you up to speed. It explains the two main types of variables: categorical variables (i.e., nominal , dichotomous and ordinal variables) and continuous variables (i.e., interval and ratio variables). It also explains the difference between independent and dependent variables , which you need to understand to create quantitative research questions.

To provide a brief explanation; a variable is not only something that you measure , but also something that you can manipulate and control for. In most undergraduate and master's level dissertations, you are only likely to measure and manipulate variables. You are unlikely to carry out research that requires you to control for variables, although some supervisors will expect this additional level of complexity. If you plan to only create descriptive research questions , you may simply have a number of dependent variables that you need to measure. However, where you plan to create comparative and/or relationship-based research questions , you will deal with both dependent and independent variables . An independent variable (sometimes called an experimental or predictor variable ) is a variable that is being manipulated in an experiment in order to observe the effect this has on a dependent variable (sometimes called an outcome variable ). For example, if we were interested in investigating the relationship between gender and attitudes towards music piracy amongst adolescents , the independent variable would be gender and the dependent variable attitudes towards music piracy . This example also highlights the need to identify the group(s) you are interested in. In this example, the group of interest are adolescents .

Once you identifying the different types of variable you are trying to measure, manipulate and/or control, as well as any groups you may be interested in, it is possible to start thinking about the way that the three types of quantitative research question can be structured . This is discussed next.

STEP THREE Select the appropriate structure for the chosen type of quantitative research question, based on the variables and/or groups involved

The structure of the three types of quantitative research question differs, reflecting the goals of the question, the types of variables, and the number of variables and groups involved. By structure , we mean the components of a research question (i.e., the types of variables, groups of interest), the number of these different components (i.e., how many variables and groups are being investigated), and the order that these should be presented (e.g., independent variables before dependent variables). The appropriate structure for each of these quantitative research questions is set out below:

Structure of descriptive research questions

  • Structure of comparative research questions
  • Structure of relationship-based research questions

There are six steps required to construct a descriptive research question: (1) choose your starting phrase; (2) identify and name the dependent variable; (3) identify the group(s) you are interested in; (4) decide whether dependent variable or group(s) should be included first, last or in two parts; (5) include any words that provide greater context to your question; and (6) write out the descriptive research question. Each of these steps is discussed in turn:

Choose your starting phrase

Identify and name the dependent variable

Identify the group(s) you are interested in

Decide whether the dependent variable or group(s) should be included first, last or in two parts

Include any words that provide greater context to your question

Write out the descriptive research question

FIRST Choose your starting phrase

You can start descriptive research questions with any of the following phrases:

How many? How often? How frequently? How much? What percentage? What proportion? To what extent? What is? What are?

Some of these starting phrases are highlighted in blue text in the examples below:

How many calories do American men and women consume per day?

How often do British university students use Facebook each week?

What are the most important factors that influence the career choices of Australian university students?

What proportion of British male and female university students use the top 5 social networks?

What percentage of American men and women exceed their daily calorific allowance?

SECOND Identify and name the dependent variable

All descriptive research questions have a dependent variable. You need to identify what this is. However, how the dependent variable is written out in a research question and what you call it are often two different things. In the examples below, we have illustrated the name of the dependent variable and highlighted how it would be written out in the blue text .

The first two examples highlight that while the name of the dependent variable is the same, namely daily calorific intake , the way that this dependent variable is written out differs in each case.

THIRD Identify the group(s) you are interested in

All descriptive research questions have at least one group , but can have multiple groups . You need to identify this group(s). In the examples below, we have identified the group(s) in the green text .

What are the most important factors that influence the career choices of Australian university students ?

The examples illustrate the difference between the use of a single group (e.g., British university students ) and multiple groups (e.g., American men and women ).

FOURTH Decide whether the dependent variable or group(s) should be included first, last or in two parts

Sometimes it makes more sense for the dependent variable to appear before the group(s) you are interested in, but sometimes it is the opposite way around. The following examples illustrate this, with the group(s) in green text and the dependent variable in blue text :

Group 1st; dependent variable 2nd:

How often do British university students use Facebook each week ?

Dependent variable 1st; group 2nd:

Sometimes, the dependent variable needs to be broken into two parts around the group(s) you are interested in so that the research question flows. Again, the group(s) are in green text and the dependent variable is in blue text :

How many calories do American men and women consume per day ?

Of course, you could choose to restructure the question above so that you do not have to split the dependent variable into two parts. For example:

How many calories are consumed per day by American men and women ?

When deciding whether the dependent variable or group(s) should be included first or last, and whether the dependent variable should be broken into two parts, the main thing you need to think about is flow : Does the question flow? Is it easy to read?

FIFTH Include any words that provide greater context to your question

Sometimes the name of the dependent variable provides all the explanation we need to know what we are trying to measure. Take the following examples:

In the first example, the dependent variable is daily calorific intake (i.e., calories consumed per day). Clearly, this descriptive research question is asking us to measure the number of calories American men and women consume per day. In the second example, the dependent variable is Facebook usage per week. Again, the name of this dependent variable makes it easy for us to understand that we are trying to measure the often (i.e., how frequently; e.g., 16 times per week) British university students use Facebook.

However, sometimes a descriptive research question is not simply interested in measuring the dependent variable in its entirety, but a particular component of the dependent variable. Take the following examples in red text :

In the first example, the research question is not simply interested in the daily calorific intake of American men and women, but what percentage of these American men and women exceeded their daily calorific allowance. So the dependent variable is still daily calorific intake, but the research question aims to understand a particular component of that dependent variable (i.e., the percentage of American men and women exceeding the recommend daily calorific allowance). In the second example, the research question is not only interested in what the factors influencing career choices are, but which of these factors are the most important.

Therefore, when you think about constructing your descriptive research question, make sure you have included any words that provide greater context to your question.

SIXTH Write out the descriptive research question

Once you have these details ? (1) the starting phrase, (2) the name of the dependent variable, (3) the name of the group(s) you are interested in, and (4) any potential joining words ? you can write out the descriptive research question in full. The example descriptive research questions discussed above are written out in full below:

In the section that follows, the structure of comparative research questions is discussed.

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9.2 Quantitative research questions

Learning objectives.

Learners will be able to…

  • Describe how research questions for exploratory, descriptive, and explanatory quantitative questions differ and how to phrase them
  • Identify the differences between and provide examples of strong and weak explanatory research questions

Quantitative descriptive questions

The type of research you are conducting will impact the research question that you ask. Probably the easiest questions to think of are quantitative descriptive questions. For example, “What is the average student debt load of MSW students?” is a descriptive question—and an important one. We aren’t trying to build a causal relationship here. We’re simply trying to describe how much debt MSW students carry. Quantitative descriptive questions like this one are helpful in social work practice as part of community scans, in which human service agencies survey the various needs of the community they serve. If the scan reveals that the community requires more services related to housing, child care, or day treatment for people with disabilities, a nonprofit office can use the community scan to create new programs that meet a defined community need.

Quantitative descriptive questions will often ask for percentage, count the number of instances of a phenomenon, or determine an average. Descriptive questions may only include one variable, such as ours about student debt load, or they may include multiple variables. Because these are descriptive questions, our purpose is not to investigate causal relationships between variables. To do that, we need to use a quantitative explanatory question.

what questions to ask in quantitative research

Quantitative explanatory questions

Most studies you read in the academic literature will be quantitative and explanatory. Why is that? If you recall from Chapter 2, explanatory research tries to build nomothetic causal relationships. They are generalizable across space and time, so they are applicable to a wide audience. The editorial board of a journal wants to make sure their content will be useful to as many people as possible, so it’s not surprising that quantitative research dominates the academic literature.

Structurally, quantitative explanatory questions must contain an independent variable and dependent variable. Questions should ask about the relationship between these variables. The standard format I was taught in graduate school for an explanatory quantitative research question is: “What is the relationship between [independent variable] and [dependent variable] for [target population]?” You should play with the wording for your research question, revising that standard format to match what you really want to know about your topic.

Let’s take a look at a few more examples of possible research questions and consider the relative strengths and weaknesses of each. Table 9.1 does just that. While reading the table, keep in mind that I have only noted what I view to be the most relevant strengths and weaknesses of each question. Certainly each question may have additional strengths and weaknesses not noted in the table. Each of these questions is drawn from student projects in my research methods classes and reflects the work of many students on their research question over many weeks.

Making it more specific

A good research question should also be specific and clear about the concepts it addresses. A student investigating gender and household tasks knows what they mean by “household tasks.” You likely also have an impression of what “household tasks” means. But are your definition and the student’s definition the same? A participant in their study may think that managing finances and performing home maintenance are household tasks, but the researcher may be interested in other tasks like childcare or cleaning. The only way to ensure your study stays focused and clear is to be specific about what you mean by a concept. The student in our example could pick a specific household task that was interesting to them or that the literature indicated was important—for example, childcare. Or, the student could have a broader view of household tasks, one that encompasses childcare, food preparation, financial management, home repair, and care for relatives. Any option is probably okay, as long as the researcher is clear on what they mean by “household tasks.” Clarifying these distinctions is important as we look ahead to specifying how your variables will be measured in Chapter 11.

Table 9.2 contains some “watch words” that indicate you may need to be more specific about the concepts in your research question.

It can be challenging to be this specific in social work research, particularly when you are just starting out your project and still reading the literature. If you’ve only read one or two articles on your topic, it can be hard to know what you are interested in studying. Broad questions like “What are the causes of chronic homelessness, and what can be done to prevent it?” are common at the beginning stages of a research project as working questions. However, moving from working questions to research questions in your research proposal requires that you examine the literature on the topic and refine your question over time to be more specific and clear. Perhaps you want to study the effect of a specific anti-homelessness program that you found in the literature. Maybe there is a particular model to fighting homelessness, like Housing First or transitional housing, that you want to investigate further. You may want to focus on a potential cause of homelessness such as LGBTQ+ discrimination that you find interesting or relevant to your practice. As you can see, the possibilities for making your question more specific are almost infinite.

Quantitative exploratory questions

In exploratory research, the researcher doesn’t quite know the lay of the land yet. If someone is proposing to conduct an exploratory quantitative project, the watch words highlighted in Table 9.2 are not problematic at all. In fact, questions such as “What factors influence the removal of children in child welfare cases?” are good because they will explore a variety of factors or causes. In this question, the independent variable is less clearly written, but the dependent variable, family preservation outcomes, is quite clearly written. The inverse can also be true. If we were to ask, “What outcomes are associated with family preservation services in child welfare?”, we would have a clear independent variable, family preservation services, but an unclear dependent variable, outcomes. Because we are only conducting exploratory research on a topic, we may not have an idea of what concepts may comprise our “outcomes” or “factors.” Only after interacting with our participants will we be able to understand which concepts are important.

Remember that exploratory research is appropriate only when the researcher does not know much about topic because there is very little scholarly research. In our examples above, there is extensive literature on the outcomes in family reunification programs and risk factors for child removal in child welfare. Make sure you’ve done a thorough literature review to ensure there is little relevant research to guide you towards a more explanatory question.

Key Takeaways

  • Descriptive quantitative research questions are helpful for community scans but cannot investigate causal relationships between variables.
  • Explanatory quantitative research questions must include an independent and dependent variable.
  • Exploratory quantitative research questions should only be considered when there is very little previous research on your topic.

TRACK 1 (IF YOU ARE CREATING A RESEARCH PROPOSAL FOR THIS CLASS):

  • Identify the type of research you are engaged in (descriptive, explanatory, or exploratory).
  • Create a quantitative research question for your project that matches with the type of research you are engaged in.

Preferably, you should be creating an explanatory research question for quantitative research.

TRACK 2 (IF YOU AREN’T CREATING A RESEARCH PROPOSAL FOR THIS CLASS):

Imagine you are studying health care disparities in communities of color and are interested in learning more about culturally appropriate interventions.

  • Based on the research question you developed in the previous section, identify what type of research you would be conducting. Is this research project descriptive, explanatory, or exploratory?
  • What factors justify your answer?

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  • How to ask quantitative survey questions: types & examples

How to ask quantitative survey questions: types & examples

Eren Eltemur

Are you looking for a way to collect objective data for your research? You can use quantitative questions to get objective data. You can use forms.app to create and customize your surveys with ready-made templates. This article will discuss creating quantitative survey questions with forms.app and the key principles of creating quantitive survey questions.

  • What is a quantitative question?

A quantitive question is an objective question about any kind of research topic. You can use these types of questions in your research surveys, and you can create a research repor t that is produced using the quantitative data based on the analysis of the responses to these quantitative survey questions.

It offers assistance when you need to generalize your study and make predictions about the future. Surveys are an excellent instrument for quantitative research because they are flexible, affordable, and allow data collection from many respondents. Quantitive questions allow researchers to collect numeric data , and it is a method to gather statistical results . 

The definition of a quantitative question

The definition of a quantitative question

Quantitative and qualitative survey questions

The goal of quantitative research is to gather data that can be represented statistically. Researchers frequently use it to compare information about particular groups . Quantitative research can be directed towards a particular audience, generally identified by demographic data like age, gender, and region , even though the survey audience is relatively large. 

Qualitative research focuses on individuals' unique behavior , including their routines or the reasons behind their choices. To understand more about sentiments, attitudes, and behaviors that are harder to measure but provide crucial extra context to quantitive research.

  • 3 Types of quantitative survey questions

Quantitive questions and their equıvelent of survey questions can be separated on a basis. The branches of quantitative questions are methods, but when you want to include these principles in your surveys, you use form builder features such as the Likert scale, open-ended questions, opinion scale, multiple choice, short text, and long text . In the end, what gives meaning to these types of questions is their way of gathering answers . Here are the types of quantitive questions and their branches: 

  • Descriptive research questions : To make a general assumption about a group of people, such as their age, sex, and maybe ethnicity, or commonly used products, researchers can use these types of questions. There are common types of descriptive research questions: 
  • Frequency questions : To understand how often a particular event occurs.
  • Percentage questions : To determine the proportion of a group, such as customers.
  • Range questions : To find the highest and the lowest point of something, such as price.
  • Profile questions : To describe a characteristic of a particular group.
  • Case study questions : To get a detailed understanding of a specific topic.
  • Comparative research questions : These types of questions are used to compare individuals or groups and can be classified as experimental or casual research.
  • Experimental : Used to test the cause-and-effect relationship of a hypothesis by interventions and manipulations.
  • Causal : To comprehend how variations in one variable affect another.
  • Relationship-based research questions : These types of questions are used to understand the link between two groups or topics. Here are some types of relationship-based research questions:
  • Correlation questions : Used to test the cause-and-effect relationship of a hypothesis without any interventions and manipulations.
  • Meta-analysis : The combined result of multiple similar studies to find patterns and inconsistencies.
  • Cross-sectional : The relationship between two things at a particular time to find a correlation.
  • Case-control : Regardless of the outcome, the relationship between particular outcomes to find patterns.
  • How to write better quantitative survey questions

Creating a better quantitative survey can be a complicated task because of the survey's nature. The intention of the questions must be chosen first to get the desired result. Clear, effective and unbiased survey questions are essential for quantitive surveys. For this reason, here is the three-step you must follow to get the desired result:

1 - Select the objective and type

You must select the type of question you want to ask. What is your intention? Are they descriptive, comparative, or relationship-based questions? By choosing your intention, you can ask the right questions and select the right words, which is the key element of your survey .

2 - Identify the variable

The dependent and independent variables, as well as the target audiences , should be decided by researchers. The many variables you seek to analyze, manipulate, or control must be identified regardless of whether you are trying to develop a descriptive, comparative, or relationship-based research question. Here are some examples for 

variables: Number of books read per year, level of education, average working hours, and time spent on social media .

You can control a variable in addition to something you can measure. You might need to assess a few dependent variables if you merely intend to develop descriptive research questions. However, you will deal with dependent and independent variables in situations where you intend to create comparative and relationship-based research questions. In an experiment, an independent variable is a variable that is changed to observe the effect.

3 - Select the appropriate structure

The aims of the questions, the types of variables, the number of variables and the groups engaged all have an influence on the structure of the three different types of quantitative research questions.

a.   Select your lead phrase.

b.   Specify the dependent variable.

c.   List the organizations in which you are interested.

d.   Choose whether to include the dependent variable or groups.

  • 16 great quantitative survey question examples

To make the steps and types clear as forms.app, we have gathered 16 quantitive question examples in surveys. Below you will see comparative, descriptive, and relationship-based research questions with specified variables and groups.

1  - What is the average life expectancy of individuals living in urban areas compared to the average life expectancy of individuals living in rural areas? 

  • Question type : Comparative
  • Variable : life expectancy
  • Groups :  "urban" and "rural"

2  - What is the average number of sick days taken by employees who work more than 40 hours per week compared to employees who work less than 40 hours per week? 

  • Variable : Number of sick days taken
  • Group : employees who work more than 40 hours per week and employees who work less than 40 hours per week

3  - What is the average height of adults in [ Asians ]? 

  • Question type : Descriptive
  • Variable : Average height
  • Group : Asians

4  - What is the average number of books read per year by people aged 18-24 compared to people aged 25-34? 

  • Variable : Number of books read per year
  • Group : people aged 18-24, people aged 25-34

  5  - What is the average number of cars per household in a [ specific country ]? 

  • Variable : average number of cars per household
  • Group : specific country

6  - What is the average temperature [ in a specific city ] during the month of July? 

  • Variable : average temperature
  • Group : specific city, the month of July

 7  - Is there a relationship between exercise frequency and weight loss? 

  • Question type : Relationship
  • Variable : Exercise frequency, Weight loss
  • Group : n/a

  8  - Is there a relationship between air pollution and lung cancer? 

  • Variable : Air pollution, Lung cancer

  9  - Is there a relationship between the level of education and average credit score? 

  • Variable : Level of education, Average credit score

10  - What is the average number of customers served per hour at fast food restaurants in the city center compared to fast food restaurants in the suburbs? 

  • Variable : Number of customers served per hour
  • Group : fast food restaurants in the city center, fast food restaurants in the suburbs

  11  - What is the average age of business owners in a specific region? 

  • Variable : average age
  • Group : business owners in a specific region

12  - What is the average commute time for residents who use public transportation compared to residents who drive alone? 

  • Variable : Commute time
  • Group : Residents who use public transportation and residents who drive alone

13  - Is there a relationship between social media usage and academic performance among college students? 

  • Variable : Social media usage, academic performance
  • Group : College students

  14  - What is the average time spent on social media per day among teenagers compared to adults? 

  • Variable : Time spent on social media per day
  • Group : Teenagers and Adults

  15  - What is the average revenue per year for small business owners compared to large business owners? 

  • Variable : Revenue per year
  • Group : Small business owners and large business owners

16  - Is there a relationship between gender and the likelihood of receiving a promotion in a specific company? 

  • Variable : Gender, the likelihood of receiving a promotion
  • Group : specific company
  • How to design a quantitative survey

Since the elements are clear now, you must clarify your topic and style, then create your survey considering your aim. For example , let's say we are creating a survey intended to learn about gender and its relationship with receiving a promotion. Our variable is gender and the likelihood of receiving a promotion, and our group is a particular company. Here are some example questions with suitable form fields you can use:

  • How satisfied are you with the current position? (Opinion scale)
  • My skills and abilities find use in my job position. (Star rating)
  • I am satisfied with my current working hours.  (Star rating)
  • When did you get hired by this company? (Short text)
  • Are there any inequalities between male and female workers? (Yes/no)
  • How likely will you be working for this organization a year from now? (Opinion scale)
  • How stressed do you feel on a regular day at work? (Opinion scale)
  • I feel that my work is seen and appreciated within my organization. (Yes/no)
  • My job allows me to grow and develop new skills. (Yes/no)
  • Do you think there is a relationship between gender and the likelihood of receiving a promotion in this company? (Yes/no)
  • Create your quantitative survey today

It can be hard to create quantitive research questions if you are unfamiliar with the method. For this reason, forms.app gathered the detailed key method of creating quantitive survey questions. You can use ready-made templates to start or just from scratch since you now know how to create your quantitive survey questions. If you want to get started quickly, take a look at these:

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Restaurant Review Survey

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Employee Satisfaction Survey Template

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Quantitative Survey Questions: Definition, Types and Examples

Quantitative survey questions

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Quantitative Survey Questions: Definition

Types of quantitative survey questions with examples, how to design quantitative survey questions.

Quantitative survey questions are defined as objective questions used to gain detailed insights from respondents about a survey research topic. The answers received for these quantitative survey questions are analyzed and a research report is generated on the basis of this

 data . These questions form the core of a survey and are used to gather numerical data to determine statistical results.

The primary stage before conducting an online survey will be to decide the objective of the survey. Every research should have an answer to this integral question: “What are the expected results of your survey?”. Once the answer to this question is figured out, the secondary stage will be deciding the type of required data: quantitative or qualitative data .

LEARN ABOUT: Survey Mistakes And How to Avoid

Deciding the data type indicates the type of information required from the research process. While qualitative data provides detailed information about the subject, quantitative data will provide effective and precise information.

Quantitative survey questions are thus, channels for collecting quantitative data . Feedback received to quantitative survey questions is related to, measured by or measuring a “quantity” or a statistic and not the “quality” of the parameter.   

Learn more: Survey Questions

Quantitative survey questions should be such that they offer respondents a medium to answer accurately. On the basis of this factor, quantitative survey questions are divided into three types:

1. Descriptive Survey Questions: Descriptive survey questions are used to gain information about a variable or multiple variables to associate a quantity to the variable.

It is the simplest type of quantitative survey questions and helps researchers in quantifying the variables by surveying a large sample of their target market.

LEARN ABOUT: Survey Sample Sizes

Most widely implemented descriptive analysis questions start with “What is this..”, “How much..”, “What is the percentage of..” and such similar questions. A popular example of a descriptive survey is an exit poll as it contains a question: “What is the percentage of candidate X winning this election?” or in a demographic segmentation survey: “How many people between the age of 18-25 exercise daily?”

Learn more: Demographic Survey Questions

Other examples of descriptive survey questions are:

  • Variable: Cuisine
  • Target Group: Mexicans
  • Variable: Facets that transform career decisions
  • Target Group: Indian students
  • Variable: Number of citizens looking for better opportunities
  • Target Group: Chinese citizens

In every example mentioned above, researchers should focus on quantifying the variable. The only factor that changes is the parameter of measurement. Every example mentions a different quantitative sample question which needs to be measured by different parameters.

LEARN ABOUT: Testimonial Questions

The answers for descriptive survey questions are definitional for the research topic and they quantify the topics of analysis. Usually, a descriptive research will require a long list of descriptive questions but experimental research or relationship-based research will be effective with a couple of descriptive survey questions.

Learn more: Quantitative Market Research & Descriptive Research vs Correlational Research

2. Comparative Survey Questions: Comparative survey questions are used to establish a comparison between two or more groups on the basis of one or more dependable variables. These quantitative survey questions begin with “What is the difference in” [dependable variable] between [two or more groups]?. This question will be enough to realize that the main objective of comparative questions is to form a comparative relationship between the groups under consideration.

LEARN ABOUT:   Structured Question & Structured Questionnaire

Comparative survey question examples:

  • Dependable Variable: Cuisine preferences
  • Comparison Groups: Mexican adults and children
  • Dependable Variable: Factors that transform career decisions
  • Comparison Groups: Indian and Australian students
  • Dependable Variable: Political notions
  • Comparison Groups: Asian and American citizens

The various groups mentioned in the above-mentioned options indicate independent variables (Mexican people or country of students). These independent variables could be based on gender questions , ethnicity or education. It is the dependable variable that determines the complexity of comparative survey questions.

LEARN ABOUT: Average Order Value

3. Relationship Survey Questions: Relationship survey questions are used to understand the association, trends and causal comparative research  relationship between two or more variables. When discussing research topics, the term relationship/causal survey questions should be carefully used since it is a widely used type of research design , i.e., experimental research – where the cause and effect between two or more variables. These questions start with “What is the relationship” [between or amongst] followed by a string of independent [gender or ethnicity] and dependent variables [career, political beliefs etc.]?

  • Dependent Variable: Food preferences
  • Independent Variable: Age
  • Relationship groups: Mexico
  • Dependent Variable: University admission
  • Independent Variable: Family income
  • Relationship groups: American students
  • Dependent Variable: Lifestyle
  • Independent Variable: Socio-economic class, ethnicity, education
  • Relationship groups: China

Learn more: What is Research?

There are four critical steps to follow while designing quantitative survey questions:

1. Select the type of quantitative survey question: The objective of the research is reflected in the chosen type of quantitative survey question. For the respondents to have a clear understanding of the survey, researchers should select the desired type of quantitative survey question.  

2. Recognize the filtered dependent and independent variables along with the target group/s: Irrespective of the type of selected quantitative survey question (descriptive, comparative or relationship based), researchers should decide on the dependent and independent variables and also the target audiences .

LEARN ABOUT: Product Survey Questions

There are four levels of measurement variables – one of which can be chosen for creating quantitative survey questions. Nominal variables indicate the names of variables, Ordinal variables indicate names and order of variables, Interval variables indicate name, order and an established interval between ordered variables and Ratio variables indicate the name, order, an established interval and also an absolute zero value.

A variable can not only be calculated but also can be manipulated and controlled. For descriptive survey questions, there can be multiple variables for which questions can be formed. In the other two types of quantitative survey questions (comparative and relationship-based), dependent and independent variables are to be decided. Independent variables are those which are manipulated in order to observe the change in the dependent variables.

Learn more: Quantitative Observation

3. Choose the right structure according to the decided type of quantitative survey question: As discussed in the previous section, appropriate structures have to be chosen to create quantitative survey questions. The intention of creating these survey questions should align with the structure of the question.

LEARN ABOUT: Level of Analysis

This structure indicates – 1) Variables 2) Groups and 3) Order in which the variables and groups should appear in the question.

4. Note the roadblocks you are trying to solve in order to create a thorough survey question: Analyze the ease of reading these questions once the right structure is in place. Will the respondents be able to easily understand the questions? – Ensure this factor before finalizing the quantitative survey questions.

Learn more:

  • Nominal Scale
  • Ordinal Scale
  • Interval Scale
  • Ratio Scale
  • Nominal Data

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Adding Quantitative Research Questions in Online Surveys

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One of the things that makes Alchemer a powerful online survey and research platform is the sheer number of question types you have access to as a user. This flexibility also allows you to add different question types to any survey, so you don’t have to choose between quantitative and qualitative questions in your survey. You can have both.

If you’re unsure of the difference between quantitative and qualitative, read the article, Does your Consumer Survey Data Paint The Whole Picture . This blog explores the differences between the two question types but here is the short version:

  • Quantitative questions will tell you Who and What.
  • Qualitative questions will tell you Why.

Quantitative questions are easier to measure and easier for survey takers to answer. Qualitative questions, on the other hand, are subjective and harder to measure. They are also harder for survey-takers to answer and too many can lead to survey fatigue.

Qualitative questions (like open textboxes or essay questions) are great for the exploratory phase of your research project or to delve deeper into a matter, but you want to use them sparingly. Don’t tire your survey-takers or yourself. Trying to analyze essay question answers to find a common theme can be arduous and time-consuming.

One way to make qualitative questions easier on both of you is to use Video Feedback questions, which allow people to respond with a video, rather than writing out their answers.

If you need hard statistics or quantifiable numbers, use quantitative questions. You can assign numeric values for easy, objective measurement and comparison.

Quantitative questions are close-ended which makes them easy to answer. You can ask a lot of these questions without tiring survey respondents. But you’ll want to mix up the question types to keep your survey interesting and your respondents engaged.

In this article we will explore the different ways to ask quantitative questions in your online survey.

How to Phrase Quantitative Questions

Quantitative questions typically start with how or what. Some common leading phrases include:

  • How frequently?
  • What percentage?
  • What proportion?
  • To what extent?

Here are some quantitative question examples:

  • How many text messages do you send a day?
  • How frequently do you text while driving?
  • How often do you send text messages while at work?

Be sure to identify all of the variables that might affect the outcome. Also be sure to include all of the groups you are interested in. Neglecting to recognize variables and groups involved will create gaps in your data that will make it hard for you to base sound decisions on.

In the example above, work and driving are variables that likely alter texting behavior. In this example, you could also collect demographic information such as age, gender, and job function so you can compare texting habits between these groups.

Quantitative Question Types

Most online survey tools offer an array of answer formats. This is good news, as these various options will engage your customers and reduce survey fatigue.

Mix up these close-ended question types to increase your response rate:

Radio Button Example:
Checkbox Example:
Drop Down Menu Example:
Drag and Drop Example:
Likert Scale Example:
Sliding Scale Example:
Star Ranking Example:
Net Promoter Score Example:
Image Select Example:
Matrix Example:

Considerations When Choosing Quantitative Question Types

While it is nice to vary your question types to keep respondents interested, it is important to consider the reporting options. Some question types report in bar and pie charts where others may not. Always test your survey and check the reports to ensure you are collecting the data in the format that best suits your needs.

Also consider the type of device your respondents will be using. Interactive question types are engaging but may not be reliable on all mobile devices. Long matrix tables can be frustrating on a mobile device since the radio buttons or checkboxes are small. Image select questions may not render properly or take too long to load.

Use “Other” as Answer Option When Necessary

Hopefully you have considered all of the relevant answer options when crafting your quantitative question. Of course, it is now always possible to include every answer option.

If you are fearful of not including an answer option, use an “Other” answer choice and provide a textbox so respondents can specify the alternative. These are easy to setup when using a radio button or checkbox question type.

If your question is well designed, the “Other” answer option should be the exception rather than the rule. Analyzing the textbox information should not be too arduous since there are likely only a few of them. If more than 50% selected “Other “ as the answer option than perhaps you needed to do some exploratory research.

Quantifiable Results

So there you have it; 10 different quantitative question types that will keep your survey interesting and your respondents engaged. But the best part is that you will have quantifiable data that you can act on! Related Articles: Does You Consumer Survey Data Paint The Whole Picture: When to Use Qualitative Vs. Quantitative Research Questions Quantitative Vs. Qualitative Research – When to Use Which Using Qualitative Exploration To Create Quantitative Surveys Using Highly Interactive Questions In Online Surveys

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35 8.3 Quantitative research questions

Learning objectives.

  • Describe how research questions for exploratory, descriptive, and explanatory quantitative questions differ and how to phrase them
  • Identify the differences between and provide examples of strong and weak explanatory research questions

Quantitative descriptive questions

The type of research you are conducting will impact the research question that you ask. Probably the easiest questions to think of are quantitative descriptive questions. For example, “What is the average student debt load of MSW students?” is a descriptive question—and an important one. We aren’t trying to build a causal relationship here. We’re simply trying to describe how much debt MSW students carry. Quantitative descriptive questions like this one are helpful in social work practice as part of community scans, in which human service agencies survey the various needs of the community they serve. If the scan reveals that the community requires more services related to housing, child care, or day treatment for people with disabilities, a nonprofit office can use the community scan to create new programs that meet a defined community need.

an illuminated street sign that reads "ask"

Quantitative descriptive questions will often ask for percentage, count the number of instances of a phenomenon, or determine an average. Descriptive questions may only include one variable, such as ours about debt load, or they may include multiple variables. Because these are descriptive questions, we cannot investigate causal relationships between variables. To do that, we need to use a quantitative explanatory question.

Quantitative explanatory questions

Most studies you read in the academic literature will be quantitative and explanatory. Why is that? If you recall from Chapter 7, explanatory research tries to build nomothetic causal relationships. They are generalizable across space and time, so they are applicable to a wide audience. The editorial board of a journal wants to make sure their content will be useful to as many people as possible, so it’s not surprising that quantitative research dominates the academic literature.

Structurally, quantitative explanatory questions must contain an independent variable and dependent variable. Questions should ask about the relationship between these variables. My standard format for an explanatory quantitative research question is: “What is the relationship between [independent variable] and [dependent variable] for [target population]?” You should play with the wording for your research question, revising it as you see fit. The goal is to make the research question reflect what you really want to know in your study.

Let’s take a look at a few more examples of possible research questions and consider the relative strengths and weaknesses of each. Table 8.1 does just that. While reading the table, keep in mind that I have only noted what I view to be the most relevant strengths and weaknesses of each question. Certainly each question may have additional strengths and weaknesses not noted in the table.

Making it more specific

A good research question should also be specific and clear about the concepts it addresses. A student investigating gender and household tasks knows what they mean by “household tasks.” You likely also have an impression of what “household tasks” means. But are your definition and the student’s definition the same? A participant in their study may think that managing finances and performing home maintenance are household tasks, but the researcher may be interested in other tasks like childcare or cleaning. The only way to ensure your study stays focused and clear is to be specific about what you mean by a concept. The student in our example could pick a specific household task that was interesting to them or that the literature indicated was important—for example, childcare. Or, the student could have a broader view of household tasks, one that encompasses childcare, food preparation, financial management, home repair, and care for relatives. Any option is probably okay, as long as the researcher is clear on what they mean by “household tasks.”

Table 8.2 contains some “watch words” that indicate you may need to be more specific about the concepts in your research question.

It can be challenging in social work research to be this specific, particularly when you are just starting out your investigation of the topic. If you’ve only read one or two articles on the topic, it can be hard to know what you are interested in studying. Broad questions like “What are the causes of chronic homelessness, and what can be done to prevent it?” are common at the beginning stages of a research project. However, social work research demands that you examine the literature on the topic and refine your question over time to be more specific and clear before you begin your study. Perhaps you want to study the effect of a specific anti-homelessness program that you found in the literature. Maybe there is a particular model to fighting homelessness, like Housing First or transitional housing that you want to investigate further. You may want to focus on a potential cause of homelessness such as LGBTQ discrimination that you find interesting or relevant to your practice. As you can see, the possibilities for making your question more specific are almost infinite.

Quantitative exploratory questions

In exploratory research, the researcher doesn’t quite know the lay of the land yet. If someone is proposing to conduct an exploratory quantitative project, the watch words highlighted in Table 8.2 are not problematic at all. In fact, questions such as “What factors influence the removal of children in child welfare cases?” are good because they will explore a variety of factors or causes. In this question, the independent variable is less clearly written, but the dependent variable, family preservation outcomes, is quite clearly written. The inverse can also be true. If we were to ask, “What outcomes are associated with family preservation services in child welfare?”, we would have a clear independent variable, family preservation services, but an unclear dependent variable, outcomes. Because we are only conducting exploratory research on a topic, we may not have an idea of what concepts may comprise our “outcomes” or “factors.” Only after interacting with our participants will we be able to understand which concepts are important.

Key Takeaways

  • Quantitative descriptive questions are helpful for community scans but cannot investigate causal relationships between variables.
  • Quantitative explanatory questions must include an independent and dependent variable.

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Home » Research Questions – Types, Examples and Writing Guide

Research Questions – Types, Examples and Writing Guide

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Research Questions

Research Questions

Definition:

Research questions are the specific questions that guide a research study or inquiry. These questions help to define the scope of the research and provide a clear focus for the study. Research questions are usually developed at the beginning of a research project and are designed to address a particular research problem or objective.

Types of Research Questions

Types of Research Questions are as follows:

Descriptive Research Questions

These aim to describe a particular phenomenon, group, or situation. For example:

  • What are the characteristics of the target population?
  • What is the prevalence of a particular disease in a specific region?

Exploratory Research Questions

These aim to explore a new area of research or generate new ideas or hypotheses. For example:

  • What are the potential causes of a particular phenomenon?
  • What are the possible outcomes of a specific intervention?

Explanatory Research Questions

These aim to understand the relationship between two or more variables or to explain why a particular phenomenon occurs. For example:

  • What is the effect of a specific drug on the symptoms of a particular disease?
  • What are the factors that contribute to employee turnover in a particular industry?

Predictive Research Questions

These aim to predict a future outcome or trend based on existing data or trends. For example :

  • What will be the future demand for a particular product or service?
  • What will be the future prevalence of a particular disease?

Evaluative Research Questions

These aim to evaluate the effectiveness of a particular intervention or program. For example:

  • What is the impact of a specific educational program on student learning outcomes?
  • What is the effectiveness of a particular policy or program in achieving its intended goals?

How to Choose Research Questions

Choosing research questions is an essential part of the research process and involves careful consideration of the research problem, objectives, and design. Here are some steps to consider when choosing research questions:

  • Identify the research problem: Start by identifying the problem or issue that you want to study. This could be a gap in the literature, a social or economic issue, or a practical problem that needs to be addressed.
  • Conduct a literature review: Conducting a literature review can help you identify existing research in your area of interest and can help you formulate research questions that address gaps or limitations in the existing literature.
  • Define the research objectives : Clearly define the objectives of your research. What do you want to achieve with your study? What specific questions do you want to answer?
  • Consider the research design : Consider the research design that you plan to use. This will help you determine the appropriate types of research questions to ask. For example, if you plan to use a qualitative approach, you may want to focus on exploratory or descriptive research questions.
  • Ensure that the research questions are clear and answerable: Your research questions should be clear and specific, and should be answerable with the data that you plan to collect. Avoid asking questions that are too broad or vague.
  • Get feedback : Get feedback from your supervisor, colleagues, or peers to ensure that your research questions are relevant, feasible, and meaningful.

How to Write Research Questions

Guide for Writing Research Questions:

  • Start with a clear statement of the research problem: Begin by stating the problem or issue that your research aims to address. This will help you to formulate focused research questions.
  • Use clear language : Write your research questions in clear and concise language that is easy to understand. Avoid using jargon or technical terms that may be unfamiliar to your readers.
  • Be specific: Your research questions should be specific and focused. Avoid broad questions that are difficult to answer. For example, instead of asking “What is the impact of climate change on the environment?” ask “What are the effects of rising sea levels on coastal ecosystems?”
  • Use appropriate question types: Choose the appropriate question types based on the research design and objectives. For example, if you are conducting a qualitative study, you may want to use open-ended questions that allow participants to provide detailed responses.
  • Consider the feasibility of your questions : Ensure that your research questions are feasible and can be answered with the resources available. Consider the data sources and methods of data collection when writing your questions.
  • Seek feedback: Get feedback from your supervisor, colleagues, or peers to ensure that your research questions are relevant, appropriate, and meaningful.

Examples of Research Questions

Some Examples of Research Questions with Research Titles:

Research Title: The Impact of Social Media on Mental Health

  • Research Question : What is the relationship between social media use and mental health, and how does this impact individuals’ well-being?

Research Title: Factors Influencing Academic Success in High School

  • Research Question: What are the primary factors that influence academic success in high school, and how do they contribute to student achievement?

Research Title: The Effects of Exercise on Physical and Mental Health

  • Research Question: What is the relationship between exercise and physical and mental health, and how can exercise be used as a tool to improve overall well-being?

Research Title: Understanding the Factors that Influence Consumer Purchasing Decisions

  • Research Question : What are the key factors that influence consumer purchasing decisions, and how do these factors vary across different demographics and products?

Research Title: The Impact of Technology on Communication

  • Research Question : How has technology impacted communication patterns, and what are the effects of these changes on interpersonal relationships and society as a whole?

Research Title: Investigating the Relationship between Parenting Styles and Child Development

  • Research Question: What is the relationship between different parenting styles and child development outcomes, and how do these outcomes vary across different ages and developmental stages?

Research Title: The Effectiveness of Cognitive-Behavioral Therapy in Treating Anxiety Disorders

  • Research Question: How effective is cognitive-behavioral therapy in treating anxiety disorders, and what factors contribute to its success or failure in different patients?

Research Title: The Impact of Climate Change on Biodiversity

  • Research Question : How is climate change affecting global biodiversity, and what can be done to mitigate the negative effects on natural ecosystems?

Research Title: Exploring the Relationship between Cultural Diversity and Workplace Productivity

  • Research Question : How does cultural diversity impact workplace productivity, and what strategies can be employed to maximize the benefits of a diverse workforce?

Research Title: The Role of Artificial Intelligence in Healthcare

  • Research Question: How can artificial intelligence be leveraged to improve healthcare outcomes, and what are the potential risks and ethical concerns associated with its use?

Applications of Research Questions

Here are some of the key applications of research questions:

  • Defining the scope of the study : Research questions help researchers to narrow down the scope of their study and identify the specific issues they want to investigate.
  • Developing hypotheses: Research questions often lead to the development of hypotheses, which are testable predictions about the relationship between variables. Hypotheses provide a clear and focused direction for the study.
  • Designing the study : Research questions guide the design of the study, including the selection of participants, the collection of data, and the analysis of results.
  • Collecting data : Research questions inform the selection of appropriate methods for collecting data, such as surveys, interviews, or experiments.
  • Analyzing data : Research questions guide the analysis of data, including the selection of appropriate statistical tests and the interpretation of results.
  • Communicating results : Research questions help researchers to communicate the results of their study in a clear and concise manner. The research questions provide a framework for discussing the findings and drawing conclusions.

Characteristics of Research Questions

Characteristics of Research Questions are as follows:

  • Clear and Specific : A good research question should be clear and specific. It should clearly state what the research is trying to investigate and what kind of data is required.
  • Relevant : The research question should be relevant to the study and should address a current issue or problem in the field of research.
  • Testable : The research question should be testable through empirical evidence. It should be possible to collect data to answer the research question.
  • Concise : The research question should be concise and focused. It should not be too broad or too narrow.
  • Feasible : The research question should be feasible to answer within the constraints of the research design, time frame, and available resources.
  • Original : The research question should be original and should contribute to the existing knowledge in the field of research.
  • Significant : The research question should have significance and importance to the field of research. It should have the potential to provide new insights and knowledge to the field.
  • Ethical : The research question should be ethical and should not cause harm to any individuals or groups involved in the study.

Purpose of Research Questions

Research questions are the foundation of any research study as they guide the research process and provide a clear direction to the researcher. The purpose of research questions is to identify the scope and boundaries of the study, and to establish the goals and objectives of the research.

The main purpose of research questions is to help the researcher to focus on the specific area or problem that needs to be investigated. They enable the researcher to develop a research design, select the appropriate methods and tools for data collection and analysis, and to organize the results in a meaningful way.

Research questions also help to establish the relevance and significance of the study. They define the research problem, and determine the research methodology that will be used to address the problem. Research questions also help to determine the type of data that will be collected, and how it will be analyzed and interpreted.

Finally, research questions provide a framework for evaluating the results of the research. They help to establish the validity and reliability of the data, and provide a basis for drawing conclusions and making recommendations based on the findings of the study.

Advantages of Research Questions

There are several advantages of research questions in the research process, including:

  • Focus : Research questions help to focus the research by providing a clear direction for the study. They define the specific area of investigation and provide a framework for the research design.
  • Clarity : Research questions help to clarify the purpose and objectives of the study, which can make it easier for the researcher to communicate the research aims to others.
  • Relevance : Research questions help to ensure that the study is relevant and meaningful. By asking relevant and important questions, the researcher can ensure that the study will contribute to the existing body of knowledge and address important issues.
  • Consistency : Research questions help to ensure consistency in the research process by providing a framework for the development of the research design, data collection, and analysis.
  • Measurability : Research questions help to ensure that the study is measurable by defining the specific variables and outcomes that will be measured.
  • Replication : Research questions help to ensure that the study can be replicated by providing a clear and detailed description of the research aims, methods, and outcomes. This makes it easier for other researchers to replicate the study and verify the results.

Limitations of Research Questions

Limitations of Research Questions are as follows:

  • Subjectivity : Research questions are often subjective and can be influenced by personal biases and perspectives of the researcher. This can lead to a limited understanding of the research problem and may affect the validity and reliability of the study.
  • Inadequate scope : Research questions that are too narrow in scope may limit the breadth of the study, while questions that are too broad may make it difficult to focus on specific research objectives.
  • Unanswerable questions : Some research questions may not be answerable due to the lack of available data or limitations in research methods. In such cases, the research question may need to be rephrased or modified to make it more answerable.
  • Lack of clarity : Research questions that are poorly worded or ambiguous can lead to confusion and misinterpretation. This can result in incomplete or inaccurate data, which may compromise the validity of the study.
  • Difficulty in measuring variables : Some research questions may involve variables that are difficult to measure or quantify, making it challenging to draw meaningful conclusions from the data.
  • Lack of generalizability: Research questions that are too specific or limited in scope may not be generalizable to other contexts or populations. This can limit the applicability of the study’s findings and restrict its broader implications.

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  • Questionnaire Design | Methods, Question Types & Examples

Questionnaire Design | Methods, Question Types & Examples

Published on July 15, 2021 by Pritha Bhandari . Revised on June 22, 2023.

A questionnaire is a list of questions or items used to gather data from respondents about their attitudes, experiences, or opinions. Questionnaires can be used to collect quantitative and/or qualitative information.

Questionnaires are commonly used in market research as well as in the social and health sciences. For example, a company may ask for feedback about a recent customer service experience, or psychology researchers may investigate health risk perceptions using questionnaires.

Table of contents

Questionnaires vs. surveys, questionnaire methods, open-ended vs. closed-ended questions, question wording, question order, step-by-step guide to design, other interesting articles, frequently asked questions about questionnaire design.

A survey is a research method where you collect and analyze data from a group of people. A questionnaire is a specific tool or instrument for collecting the data.

Designing a questionnaire means creating valid and reliable questions that address your research objectives , placing them in a useful order, and selecting an appropriate method for administration.

But designing a questionnaire is only one component of survey research. Survey research also involves defining the population you’re interested in, choosing an appropriate sampling method , administering questionnaires, data cleansing and analysis, and interpretation.

Sampling is important in survey research because you’ll often aim to generalize your results to the population. Gather data from a sample that represents the range of views in the population for externally valid results. There will always be some differences between the population and the sample, but minimizing these will help you avoid several types of research bias , including sampling bias , ascertainment bias , and undercoverage bias .

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what questions to ask in quantitative research

Questionnaires can be self-administered or researcher-administered . Self-administered questionnaires are more common because they are easy to implement and inexpensive, but researcher-administered questionnaires allow deeper insights.

Self-administered questionnaires

Self-administered questionnaires can be delivered online or in paper-and-pen formats, in person or through mail. All questions are standardized so that all respondents receive the same questions with identical wording.

Self-administered questionnaires can be:

  • cost-effective
  • easy to administer for small and large groups
  • anonymous and suitable for sensitive topics

But they may also be:

  • unsuitable for people with limited literacy or verbal skills
  • susceptible to a nonresponse bias (most people invited may not complete the questionnaire)
  • biased towards people who volunteer because impersonal survey requests often go ignored.

Researcher-administered questionnaires

Researcher-administered questionnaires are interviews that take place by phone, in-person, or online between researchers and respondents.

Researcher-administered questionnaires can:

  • help you ensure the respondents are representative of your target audience
  • allow clarifications of ambiguous or unclear questions and answers
  • have high response rates because it’s harder to refuse an interview when personal attention is given to respondents

But researcher-administered questionnaires can be limiting in terms of resources. They are:

  • costly and time-consuming to perform
  • more difficult to analyze if you have qualitative responses
  • likely to contain experimenter bias or demand characteristics
  • likely to encourage social desirability bias in responses because of a lack of anonymity

Your questionnaire can include open-ended or closed-ended questions or a combination of both.

Using closed-ended questions limits your responses, while open-ended questions enable a broad range of answers. You’ll need to balance these considerations with your available time and resources.

Closed-ended questions

Closed-ended, or restricted-choice, questions offer respondents a fixed set of choices to select from. Closed-ended questions are best for collecting data on categorical or quantitative variables.

Categorical variables can be nominal or ordinal. Quantitative variables can be interval or ratio. Understanding the type of variable and level of measurement means you can perform appropriate statistical analyses for generalizable results.

Examples of closed-ended questions for different variables

Nominal variables include categories that can’t be ranked, such as race or ethnicity. This includes binary or dichotomous categories.

It’s best to include categories that cover all possible answers and are mutually exclusive. There should be no overlap between response items.

In binary or dichotomous questions, you’ll give respondents only two options to choose from.

White Black or African American American Indian or Alaska Native Asian Native Hawaiian or Other Pacific Islander

Ordinal variables include categories that can be ranked. Consider how wide or narrow a range you’ll include in your response items, and their relevance to your respondents.

Likert scale questions collect ordinal data using rating scales with 5 or 7 points.

When you have four or more Likert-type questions, you can treat the composite data as quantitative data on an interval scale . Intelligence tests, psychological scales, and personality inventories use multiple Likert-type questions to collect interval data.

With interval or ratio scales , you can apply strong statistical hypothesis tests to address your research aims.

Pros and cons of closed-ended questions

Well-designed closed-ended questions are easy to understand and can be answered quickly. However, you might still miss important answers that are relevant to respondents. An incomplete set of response items may force some respondents to pick the closest alternative to their true answer. These types of questions may also miss out on valuable detail.

To solve these problems, you can make questions partially closed-ended, and include an open-ended option where respondents can fill in their own answer.

Open-ended questions

Open-ended, or long-form, questions allow respondents to give answers in their own words. Because there are no restrictions on their choices, respondents can answer in ways that researchers may not have otherwise considered. For example, respondents may want to answer “multiracial” for the question on race rather than selecting from a restricted list.

  • How do you feel about open science?
  • How would you describe your personality?
  • In your opinion, what is the biggest obstacle for productivity in remote work?

Open-ended questions have a few downsides.

They require more time and effort from respondents, which may deter them from completing the questionnaire.

For researchers, understanding and summarizing responses to these questions can take a lot of time and resources. You’ll need to develop a systematic coding scheme to categorize answers, and you may also need to involve other researchers in data analysis for high reliability .

Question wording can influence your respondents’ answers, especially if the language is unclear, ambiguous, or biased. Good questions need to be understood by all respondents in the same way ( reliable ) and measure exactly what you’re interested in ( valid ).

Use clear language

You should design questions with your target audience in mind. Consider their familiarity with your questionnaire topics and language and tailor your questions to them.

For readability and clarity, avoid jargon or overly complex language. Don’t use double negatives because they can be harder to understand.

Use balanced framing

Respondents often answer in different ways depending on the question framing. Positive frames are interpreted as more neutral than negative frames and may encourage more socially desirable answers.

Use a mix of both positive and negative frames to avoid research bias , and ensure that your question wording is balanced wherever possible.

Unbalanced questions focus on only one side of an argument. Respondents may be less likely to oppose the question if it is framed in a particular direction. It’s best practice to provide a counter argument within the question as well.

Avoid leading questions

Leading questions guide respondents towards answering in specific ways, even if that’s not how they truly feel, by explicitly or implicitly providing them with extra information.

It’s best to keep your questions short and specific to your topic of interest.

  • The average daily work commute in the US takes 54.2 minutes and costs $29 per day. Since 2020, working from home has saved many employees time and money. Do you favor flexible work-from-home policies even after it’s safe to return to offices?
  • Experts agree that a well-balanced diet provides sufficient vitamins and minerals, and multivitamins and supplements are not necessary or effective. Do you agree or disagree that multivitamins are helpful for balanced nutrition?

Keep your questions focused

Ask about only one idea at a time and avoid double-barreled questions. Double-barreled questions ask about more than one item at a time, which can confuse respondents.

This question could be difficult to answer for respondents who feel strongly about the right to clean drinking water but not high-speed internet. They might only answer about the topic they feel passionate about or provide a neutral answer instead – but neither of these options capture their true answers.

Instead, you should ask two separate questions to gauge respondents’ opinions.

Strongly Agree Agree Undecided Disagree Strongly Disagree

Do you agree or disagree that the government should be responsible for providing high-speed internet to everyone?

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You can organize the questions logically, with a clear progression from simple to complex. Alternatively, you can randomize the question order between respondents.

Logical flow

Using a logical flow to your question order means starting with simple questions, such as behavioral or opinion questions, and ending with more complex, sensitive, or controversial questions.

The question order that you use can significantly affect the responses by priming them in specific directions. Question order effects, or context effects, occur when earlier questions influence the responses to later questions, reducing the validity of your questionnaire.

While demographic questions are usually unaffected by order effects, questions about opinions and attitudes are more susceptible to them.

  • How knowledgeable are you about Joe Biden’s executive orders in his first 100 days?
  • Are you satisfied or dissatisfied with the way Joe Biden is managing the economy?
  • Do you approve or disapprove of the way Joe Biden is handling his job as president?

It’s important to minimize order effects because they can be a source of systematic error or bias in your study.

Randomization

Randomization involves presenting individual respondents with the same questionnaire but with different question orders.

When you use randomization, order effects will be minimized in your dataset. But a randomized order may also make it harder for respondents to process your questionnaire. Some questions may need more cognitive effort, while others are easier to answer, so a random order could require more time or mental capacity for respondents to switch between questions.

Step 1: Define your goals and objectives

The first step of designing a questionnaire is determining your aims.

  • What topics or experiences are you studying?
  • What specifically do you want to find out?
  • Is a self-report questionnaire an appropriate tool for investigating this topic?

Once you’ve specified your research aims, you can operationalize your variables of interest into questionnaire items. Operationalizing concepts means turning them from abstract ideas into concrete measurements. Every question needs to address a defined need and have a clear purpose.

Step 2: Use questions that are suitable for your sample

Create appropriate questions by taking the perspective of your respondents. Consider their language proficiency and available time and energy when designing your questionnaire.

  • Are the respondents familiar with the language and terms used in your questions?
  • Would any of the questions insult, confuse, or embarrass them?
  • Do the response items for any closed-ended questions capture all possible answers?
  • Are the response items mutually exclusive?
  • Do the respondents have time to respond to open-ended questions?

Consider all possible options for responses to closed-ended questions. From a respondent’s perspective, a lack of response options reflecting their point of view or true answer may make them feel alienated or excluded. In turn, they’ll become disengaged or inattentive to the rest of the questionnaire.

Step 3: Decide on your questionnaire length and question order

Once you have your questions, make sure that the length and order of your questions are appropriate for your sample.

If respondents are not being incentivized or compensated, keep your questionnaire short and easy to answer. Otherwise, your sample may be biased with only highly motivated respondents completing the questionnaire.

Decide on your question order based on your aims and resources. Use a logical flow if your respondents have limited time or if you cannot randomize questions. Randomizing questions helps you avoid bias, but it can take more complex statistical analysis to interpret your data.

Step 4: Pretest your questionnaire

When you have a complete list of questions, you’ll need to pretest it to make sure what you’re asking is always clear and unambiguous. Pretesting helps you catch any errors or points of confusion before performing your study.

Ask friends, classmates, or members of your target audience to complete your questionnaire using the same method you’ll use for your research. Find out if any questions were particularly difficult to answer or if the directions were unclear or inconsistent, and make changes as necessary.

If you have the resources, running a pilot study will help you test the validity and reliability of your questionnaire. A pilot study is a practice run of the full study, and it includes sampling, data collection , and analysis. You can find out whether your procedures are unfeasible or susceptible to bias and make changes in time, but you can’t test a hypothesis with this type of study because it’s usually statistically underpowered .

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

  • Student’s  t -distribution
  • Normal distribution
  • Null and Alternative Hypotheses
  • Chi square tests
  • Confidence interval
  • Quartiles & Quantiles
  • Cluster sampling
  • Stratified sampling
  • Data cleansing
  • Reproducibility vs Replicability
  • Peer review
  • Prospective cohort study

Research bias

  • Implicit bias
  • Cognitive bias
  • Placebo effect
  • Hawthorne effect
  • Hindsight bias
  • Affect heuristic
  • Social desirability bias

A questionnaire is a data collection tool or instrument, while a survey is an overarching research method that involves collecting and analyzing data from people using questionnaires.

Closed-ended, or restricted-choice, questions offer respondents a fixed set of choices to select from. These questions are easier to answer quickly.

Open-ended or long-form questions allow respondents to answer in their own words. Because there are no restrictions on their choices, respondents can answer in ways that researchers may not have otherwise considered.

A Likert scale is a rating scale that quantitatively assesses opinions, attitudes, or behaviors. It is made up of 4 or more questions that measure a single attitude or trait when response scores are combined.

To use a Likert scale in a survey , you present participants with Likert-type questions or statements, and a continuum of items, usually with 5 or 7 possible responses, to capture their degree of agreement.

You can organize the questions logically, with a clear progression from simple to complex, or randomly between respondents. A logical flow helps respondents process the questionnaire easier and quicker, but it may lead to bias. Randomization can minimize the bias from order effects.

Questionnaires can be self-administered or researcher-administered.

Researcher-administered questionnaires are interviews that take place by phone, in-person, or online between researchers and respondents. You can gain deeper insights by clarifying questions for respondents or asking follow-up questions.

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May 12, 2010

Becoming a Critical Reader: Questions to Ask About Quantitative Research

By: Andrea D. Lythgoe, LCCE | 0 Comments

Quantitative research seeks to prove something through experimentation and statistics. Once you've determined that what you have here is an original piece of quantitative research and you've already considered the basic questions here , you're ready for the specific questions:

1. How many groups are compared? Did the authors show that the groups are statistically similar? Look for a table showing things like basic demographic information comparing the groups. Some studies will only have one group. In this case, the authors may be comparing the group at two different times (like before and after a treatment) or they may be comparing the study group to the general population using existing data. If the authors are using existing population data as a control, they should demonstrate that the study group is similar to the general population.

2. Did the authors prove correlation or causation? This is a very important distinction to understand.

Correlation just demonstrates that two things tend to happen together. They could be completely unrelated. To use a fictional example, you might find a correlation between mothers with blue eyes and the number of towels used in the labor room, but it does not mean that the blue eyes are the reason for the increased towel use. A correlation can be positive (when the rate of variable A increases, so does the rate of variable B) or negative (when the rate of A increases, the rate of B decreases). You'll sometimes hear things described as 'associated with' - this is generally referring to correlation.

Causation requires statistics and probability to determine if the connection is likely to be because of the variable tested. Researchers must create two groups of participants who are similar in every way except the intervention that they are testing. This can be done by randomizing participants into two groups or using statistical procedures to control for differences.

(This is very much an oversimplification. I'll be doing a series on statistics later that will explore these concepts further.)

3. Are the tables, charts, and graphs understandable ? Do they relate to the conclusions? Could they mislead someone who does not read the text?

4. Is this study population applicable to my practice or situation? Look at the criteria for including (or excluding) the study population. Read it over and see who the study was done with. A study done only with low risk first time moms may not be applicable to a diabetic woman pregnant with her fourth baby. On the flip side, sometimes studies that look at a specific population can provide very useful and helpful information for that specific population. Just make sure you know what the study population is, and recognize that you cannot accurately apply that information to a wider or different group.

5. Are the findings really significant? There is a difference between statistical significance and clinical significance. A student once showed me a study of castor oil induction where the authors reported a significant difference in APGAR scores between the two groups. While the calculated p value was less than .05, the two groups average Apgar scores were 9.78 and 9.71. The babies in BOTH groups had good outcomes - the difference simply didn't mean much clinically.

6. Is the study size sufficient? In quantitative research, a bigger sample size usually helps. The more you have in the study, you're better able to find statistical differences. It isn't just the overall study size, either. Many studies will run analysis of smaller subgroups. So to use another hypothetical example, a study looking at a new drug might have 5,000 women in the study, but if the authors report that 'among women who have 6 or more previous pregnancies, the risk is lowered' - you should find out how many women are in that subgroup. If there were only 15 in that subgroup, it might be hard to make a valid conclusion. It is very common to look at subgroups by the number of previous pregnancies, by race, or by other categories.

7. What is being tested, and what is it being compared to? Some studies will have one or more experimental groups and a 'control' group as a comparison. This control group will either have no treatment, a placebo treatment, or the current 'standard' treatment. Ethically, you cannot test a new cancer drug by giving cancer patients in the control group no treatment, but you can compare a new drug against the current treatment. Make sure that (within the bounds of ethics) the researchers have chosen an appropriate comparison group.

8. What were the outcomes measured? How were they measured? Every study has at least one independent variable - the thing(s) the researchers are trying to learn about. They choose certain things, called outcomes (or dependant variables) to watch for. An example of this would be an epidural study that compares those who have early epidurals with late epidurals. The timing of the epidural would be the independent variable. The outcomes are chosen by the researcher, and could include things like cesarean rate, epidural complications, APGAR scores, etc. The study should clearly outline which outcomes they were interested in and how they were measured.

9. If applicable, did the researchers do a good job of 'blinding'? Blinding is the term for keeping from the study participants and staff which group they are in. This is common in drug trials. Sometimes people are helped by simply believing that something will help - the well known 'placebo effect'. If the participant does not know which drug they are taking (experimental drug, standard treatment, or 'fake' drug with no effects) the researcher can better determine which effects truly are from the drug being tested. The staff is also blinded whenever possible to avoid accidentally or subconsciously biasing the result. Sometimes blinding is simply not possible, but whenever possible, it is a helpful technique.

10. And finally, what does this mean for me? That will vary widely based on your personal situation. As a reader, you may be a nurse, midwife, childbirth educator, doula, doctor, or parent. You may have more than one role. Carefully think about how this may - or may not - apply to you in your various roles.

Remember that not every study is perfect. Finding a minor flaw in a study does not necessarily invalidate the whole study. You as the reader need to remember to be objective and ask yourself if the study does a good enough job of showing what it set out to do. Because of our differing perspectives and biases, it is possible to come to a different conclusion than another reader. Also, each study should be considered in the context of all the other research done on the topic. Right now that seems overwhelming, doesn't it? Our next type of article, literature reviews, will give you insight on how you can view studies in the context of other research.

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Andrea Lythgoe

Andrea D. Lythgoe, LCCE

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Quantitative market research questions to ask for actionable insights

Types of quantitative market research questions, 36 quantitative research questions and examples, how to write your own quantitative market research questions, how to collect insightful data from your quantitative surveys, receive quantitative insights in weeks, not months.

There’s a big difference between asking “Why do you like our product?” and “On a scale of 1-10, how much do you like our product?” But both ways of asking are valuable in their own way.

Knowing your audience is not about guesswork or intuition, it is about concrete data. And while it’s valuable to learn the ‘why’ behind the ‘what’ with qualitative research, quantitative research is just as necessary — to spot trends, patterns and more.

Unlike qualitative research, which explores attitudes, opinions, and motivations through open-ended questions, quantitative research zeroes in on the numbers (see what we did there?). It’s the difference between gathering general opinions and collecting measurable, specific data.

But when is this approach the way to go? For starters, whenever you need to track factors over time, such as customer satisfaction. Or when assessing the popularity of a potential product feature, understanding demographic preferences, or analyzing consumer purchasing behavior in different locations.

Quantitative research reveals the impact and scale of sentiments for better decision-making. It’s also valuable when you’re looking to quantify the extent of a trend, measure the impact of a marketing campaign, or pin down the specifics of consumer behavior.

But how do you ask quantitative market research questions that don’t just scratch the surface? We’re here to give you some great examples of quantitative survey questions.

In the US? Check out these research platforms

Here are the top market research platforms in the US for reliable insights – check them out and start getting your insights today!

When thinking of quantitative market research questions, people often think ‘ ah, numbers ‘. But there’s more than meets the eye. Here’s how you can categorize the different types of quantitative research questions:

Descriptive quantitative research questions

These are your what , when , and how many types of questions. They help you sketch out the basic landscape of your market. For example, “How often do you shop online in a month?” or “What is your preferred method of payment while shopping online?” When you give answers people can select, it is quantifiable data. That’s different from asking: ”describe what a day out shopping looks like for you”, which is a qualitative question.

Comparative quantitative survey questions

These questions measure differences or changes over time or between groups. For instance, “How has your spending on online shopping changed since last year?” Comparative questions help you understand the dynamics and shifts in your market. Remember that you’re not just trying to find overlap: it’s just as important to know what differences there are.

Relationship-based quantitative survey questions

These questions aim to uncover correlations or relationships between two or more variables. They can reveal insights like, “Is there a link between age and the likelihood of using mobile payments?” These questions help you understand the deeper connections within your market, as well as test assumptions, as long as you dare to ask questions that challenge what you’re hoping to find.

Now, a quick note on reducing bias in quantitative survey questions . Here are some key points to remember:

  • The key is in how you frame your questions.
  • Always aim for neutrality.
  • Avoid leading questions that suggest a particular answer.
  • Be specific and clear to avoid confusion.
  • Consider the order of your questions, as earlier questions can influence responses to later ones.

And finally, test your survey with a small group before a full rollout, to catch and correct any unintentional bias. This way, you ensure the data you collect is as accurate and reliable as possible, giving you the best insights to make those crucial business decisions.

If you want to make a quantitative survey that hits the spot, don’t just ask generic questions. We’re here with some examples that you can adapt to make your research a success.

Descriptive market research questions

With a descriptive quantitative research question, you can quickly get the most important info for your respondents on anything ranging from buying frequency to satisfaction levels.

  • Insight : this question reveals the frequency of use, indicating customer dependency on your product or service.
  • Benefit : understanding usage patterns can guide inventory management and marketing strategies.
  • Insight : reveals the communication channels most favored by your audience.
  • Benefit : tailor your customer service and marketing outreach to your customers’ preferred channels.
  • Insight : provides an average spending figure for budget allocation in that category.
  • Benefit : helps in pricing strategies and identifying the most lucrative customer segments.
  • Insight : uncovers patterns in online shopping behavior.
  • Benefit : optimizes the timing of online marketing campaigns and promotions.
  • Insight : identifies the most effective channels for brand discovery.
  • Benefit : informs where to allocate advertising spend for maximum impact.
  • Insight : measures the likelihood (not effectiveness!) of word-of-mouth referrals.
  • Benefit : assesses customer satisfaction and the potential for organic growth.
  • Insight : highlights your unique selling points from the customer’s perspective.
  • Benefit : guides messaging to emphasize what customers value most about your brand.
  • Insight : offers a quantifiable measure of customer service satisfaction.
  • Benefit : identifies areas for improvement in customer support.
  • Insight : sheds light on the most popular aspects of your product.
  • Benefit : informs product development and feature enhancement.
  • Insight : uncovers the key motivators behind purchasing decisions.
  • Benefit : helps create targeted marketing campaigns to focus on these driving factors. 

Comparative market research questions

If you want to analyze and compare different variables, these questions can help.

  • Insight : highlights changes in consumer spending habits over time.
  • Benefit : useful for identifying trends and shifts in consumer behavior, aiding in long-term planning. Especially valuable if you add qualitative insights to this quantitative data.
  • Insight : compares consumer preferences between different shopping channels.
  • Benefit : guides omnichannel marketing strategies and resource allocation.
  • Insight : tracks changing consumer values and preferences over time.
  • Benefit : useful for aligning product development and marketing with evolving consumer values.
  • Insight : compares the weight of price versus brand in purchasing decisions.
  • Benefit : informs pricing strategies and brand positioning efforts.
  • Insight : evaluates customer perception of marketing efforts in product packaging.
  • Benefit : assesses the impact of packaging on brand image and customer approval.

What are the top research platforms in the UK?

Here’s our list of the pros and cons of key market research platforms for UK brands

Relationship-based questions for quantitative research

In quantitative research, especially when exploring relationship-based aspects, the key is not to cram multiple inquiries into one question but to ask them sequentially.

This approach allows for a clearer and more focused response to each individual question. Later, during the analysis phase, you can then correlate the responses to uncover relationships between different variables.

For instance, instead of asking, “How often do you use our product and how satisfied are you with it?”, split this into two separate questions:

  • “How often do you use our product (daily, weekly, monthly)?”
  • “On a scale of 1-10, how satisfied are you with our product?”

By asking these questions separately, you ensure that respondents clearly focus on each aspect without being overwhelmed or confused by a dual-focused question. This approach yields more accurate and reliable data.

After the survey, you can analyze the results to see if there’s a correlation between usage frequency and satisfaction levels.

Here are some examples of combinations that can work well:

  • What is your age group?
  • Insight : correlates age with shopping preferences.
  • Benefit : you can tailor marketing and sales strategies to different age demographics based on their preferred shopping channels.
  • How long have you been using our products/services?
  • Insight : links customer tenure with brand loyalty.
  • Benefit : assesses the impact of long-term use on loyalty, informing customer retention initiatives.
  • What is your approximate annual income?
  • Insight : examines the relationship between income levels and purchasing behavior for premium products.
  • Benefit : guides product and pricing strategies targeting different income segments.
  • How often do you use social media for product discovery?
  • Insight : assesses if frequent social media use for product discovery actually influences online shopping behavior.
  • Benefit : informs the effectiveness of social media marketing in driving online sales in your target market.
  • How would you rate your satisfaction with our post-purchase customer service (scale of 0-10)?
  • Insight : links the level of service post-purchase with the likelihood of repeat purchases.
  • Benefit : identifies if customer service is negatively or positively affecting repeat custom rates.

Brand tracking questions for quantitative insights

One thing you should definitely gather numerical data on, is your brand’s health. Just like your own health, stats, and numbers matter and can show you where to further investigate to ask qualitative research questions about. Learn if your brand stands strong through market trends and gain insights on whether your brand is growing in terms of awareness — and in which segments.

  • Insight : measures brand awareness among the target audience.
  • Benefit : helps assess the effectiveness of your marketing and branding efforts.
  • Insight : evaluates brand loyalty and the potential for organic growth through word-of-mouth.
  • Benefit : indicates customer satisfaction and the potential for brand advocacy.
  • Insight: Identifies the most effective channels for brand discovery.
  • Benefit: Informs where to focus marketing efforts for increased brand exposure.
  • Insight: Measures brand visibility and frequency of encounters with the brand.
  • Benefit: Helps evaluate the reach and frequency of marketing campaigns.
  • Insight: Determines which brand values resonate most with the audience.
  • Benefit: Aids in refining brand messaging and aligning it with customer values.

Quantitative consumer segmentation questions

Quantitative questions about customer segments can go beyond age group and gender. King Charles III is the same age as Ozzy Osbourne – would you say they’re very similar?

what questions to ask in quantitative research

It is vital that you look at more variables so you can really tell the difference between your respondents, and make informed decisions based on the whole truth. Putting these consumer profiling questions and answers in specific ranges helps you create segments to tailor your marketing and customer experience for, rather than just aiming at the entire population.

  • Insight : helps understand the economic demographics of your customers.
  • Benefit : assists in pricing strategies and identifying which income groups are most engaged with your brand.
  • Insight : reveals geographical spread and regional preferences.
  • Benefit : guides regional marketing efforts and product distribution strategies.
  • Insight : helps categorize customers by education level.
  • Benefit : useful for tailoring communication and content complexity to different education backgrounds.
  • Insight : provides insights into the professional background of your customers.
  • Benefit : helps in creating industry-specific marketing campaigns and products.
  • Insight : gives an idea of household size and composition.
  • Benefit : useful for targeting products and services aimed at families or individuals.
  • Insight : identifies customers who are parents of minors (which is different from parents of young adults, or even grown adults).
  • Benefit : informs product and marketing strategies aimed at families with children.

Okay, so now you got the gist of it and have seen what quantitative questions can look like — as they come in all shapes and sizes. But they might feel too generic for your research, or you’re looking for something specific.

Here’s how you can whip up your own quantitative questions that deliver the insights you need for data-driven decisions.

Identify the key variables you need to measure

Start by pinpointing exactly what you want to know. Is it customer satisfaction, buying behavior, or brand awareness? Determining the specific variables you need to measure sets the foundation for your entire survey.

Choose the right survey distribution method

Think about how your questions will reach your audience. Will it be online through email or social media, over the phone, or in person? Your method should align with where your target audience is most active and responsive.

Make sure your questions are crystal-clear and unequivocally unbiased

We’ve mentioned it earlier, and we’ll do it again if we have to. The way you phrase your questions can make or break your survey. Aim for clarity and simplicity – questions should be easy to understand and answer. Avoid leading or loaded questions that might sway a respondent’s answer. Remember: it’s a survey, not a sales pitch.

Know where to ask for more detailed information and qualitative data

Quantitative market research questions only tell part of the story. If you see interesting trends in say purchase behavior or price sensitivity, or a particular product gets a bad rating, dig a little deeper. Follow up important questions with qualitative research questions to analyze what’s going on behind the numbers.

If you don’t want to end up with a pile of quantitative data that doesn’t do much for you or breaks the bank unnecessarily, it’s vital you choose a form of distributing the survey that makes sense. You can work with UK market research companies to outsource it all, or do it yourself. Here’s a brief look at the pros and cons of popular methods:

Telephone surveys:

  • Pros : good for less tech-savvy demographics.
  • Cons : time-consuming, potentially costly, and declining response rates. They might be better for qualitative research.

In-person surveys:

  • Pros : also avoids any confusion with tech.
  • Cons : logistically demanding and expensive, not suited for quick data collection.

Online survey software:

  • Pros : cost-effective, broad reach, real-time data analysis, and versatile formats.
  • Cons : it’s extra important to pay close attention to survey design, so people don’t get the urge to give false answers just to get to the end.

The choice is yours, but generally, quantitative research thrives when done with online surveys and it’s the go-to method for most international market research . And here at Attest, we help you get even more out of it by giving you a chock-full toolkit. From various types of questions to robust analytical tools (and a dedicated research expert for when you need a little extra help) — we set you up for measurable success.

Speed and accuracy in market research matter — but we don’t want you to sacrifice quality. With Attest, you get fast, actionable and high-quality insights.

Which market analysis tool is right for you?

Check our rundown of the top platforms for market analysis – and start making better decisions with reliable insights in no time!

what questions to ask in quantitative research

VP Customer Success 

Sam joined Attest in 2019 and leads the Customer Research Team. Sam and her team support brands through their market research journey, helping them carry out effective research and uncover insights to unlock new areas for growth.

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IMAGES

  1. Quantitative research questions: Types, tips & examples

    what questions to ask in quantitative research

  2. Quantitative Research Questions Examples

    what questions to ask in quantitative research

  3. Example of Research Questions for a Quantitative Study Type 1a 1a: To

    what questions to ask in quantitative research

  4. How to ask quantitative survey questions: types & examples

    what questions to ask in quantitative research

  5. Week 12: Quantitative Research Methods

    what questions to ask in quantitative research

  6. Quantitative Research Questions Examples

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COMMENTS

  1. How to Write Quantitative Research Questions: Types With Examples

    It is the most effortless way to measure the particular variable (single or multiple variables) you are interested in on a large scale. Usually, descriptive research questions begin with " how much," "how often," "what percentage," "what proportion," etc. Examples of descriptive research questions include: Questions. Variable.

  2. Quantitative research questions: Types, tips & examples

    100+ Quantitative research questions to ask in your research surveys. In your next survey, you can use any of the questions below, or you can create your own. If you use smart questions focused on a subject or aspect, it will make it easier for you to make an informed analysis at the end. Now, let us start with the first one:

  3. What Are Quantitative Survey Questions? Types and Examples

    Descriptive research questions (also known as usage and attitude, or, U&A questions) seek a general indication or prediction about how a group of people behaves or will behave, how that group is characterized, or how a group thinks. For example, a business might want to know what portion of adult men shave, and how often they do so.

  4. A Practical Guide to Writing Quantitative and Qualitative Research

    INTRODUCTION. Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses.1,2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results.3,4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the ...

  5. 10 Research Question Examples to Guide your Research Project

    The first question asks for a ready-made solution, and is not focused or researchable. The second question is a clearer comparative question, but note that it may not be practically feasible. For a smaller research project or thesis, it could be narrowed down further to focus on the effectiveness of drunk driving laws in just one or two countries.

  6. Quantitative Research Questions

    A research question is the driving question (s) behind your research. It should be about an issue that you are genuinely curious and/or passionate about. A good research question is: Clear: The purpose of the study should be clear to the reader, without additional explanation. Focused: The question is specific.

  7. 98 Quantitative Research Questions & Examples

    Quantitative market research questions tell you the what, how, when, and where of a subject. From trendspotting to identifying patterns or establishing averages-using quantitative data is a clear and effective way to start solving business problems. Types of quantitative research questions. Quantitative market research questions are divided ...

  8. How to structure quantitative research questions

    Structure of descriptive research questions. There are six steps required to construct a descriptive research question: (1) choose your starting phrase; (2) identify and name the dependent variable; (3) identify the group (s) you are interested in; (4) decide whether dependent variable or group (s) should be included first, last or in two parts ...

  9. 4.3 Quantitative research questions

    Quantitative descriptive questions. The type of research you are conducting will impact the research question that you ask. Probably the easiest questions to think of are quantitative descriptive questions. For example, "What is the average student debt load of MSW students?" is a descriptive question—and an important one.

  10. Writing Strong Research Questions

    A good research question is essential to guide your research paper, dissertation, or thesis. All research questions should be: Focused on a single problem or issue. Researchable using primary and/or secondary sources. Feasible to answer within the timeframe and practical constraints. Specific enough to answer thoroughly.

  11. 9.2 Quantitative research questions

    Quantitative descriptive questions will often ask for percentage, count the number of instances of a phenomenon, or determine an average. Descriptive questions may only include one variable, such as ours about student debt load, or they may include multiple variables. Because these are descriptive questions, our purpose is not to investigate ...

  12. What Is Quantitative Research?

    Quantitative research is the process of collecting and analyzing numerical data. It can be used to find patterns and averages, make predictions, test causal relationships, and generalize results to wider populations. ... Ask questions of a group of people in-person, over-the-phone or online. ...

  13. 8.3 Quantitative research questions

    Quantitative descriptive questions will often ask for figures such as percentages, sums, or averages. Descriptive questions may only include one variable, such as ours included the variable of student debt, or they may include multiple variables. When asking a descriptive question, we cannot investigate causal relationships between variables.

  14. 9.3: Quantitative research questions

    The type of research you are conducting will impact the research question that you ask. Probably the easiest questions to think of are quantitative descriptive questions. For example, "What is the average student debt load of MSW students?" is a descriptive question—and an important one.

  15. How to ask quantitative survey questions: types & examples

    Quantitative and qualitative survey questions. The goal of quantitative research is to gather data that can be represented statistically. Researchers frequently use it to compare information about particular groups.Quantitative research can be directed towards a particular audience, generally identified by demographic data like age, gender, and region, even though the survey audience is ...

  16. Quantitative Survey Questions: Definition, Types and Examples

    Quantitative survey questions are defined as objective questions used to gain detailed insights from respondents about a survey research topic. The answers received for these quantitative survey questions are analyzed and a research report is generated on the basis of this. data. These questions form the core of a survey and are used to gather ...

  17. New Quantitative Research Questions in Online Surveys

    Quantitative questions will tell you Who and What. Qualitative questions will tell you Why. Quantitative questions are easier to measure and easier for survey takers to answer. Qualitative questions, on the other hand, are subjective and harder to measure. They are also harder for survey-takers to answer and too many can lead to survey fatigue.

  18. 8.3 Quantitative research questions

    Quantitative descriptive questions will often ask for percentage, count the number of instances of a phenomenon, or determine an average. Descriptive questions may only include one variable, such as ours about debt load, or they may include multiple variables. Because these are descriptive questions, we cannot investigate causal relationships ...

  19. Research Questions

    Definition: Research questions are the specific questions that guide a research study or inquiry. These questions help to define the scope of the research and provide a clear focus for the study. Research questions are usually developed at the beginning of a research project and are designed to address a particular research problem or objective.

  20. Questionnaire Design

    Revised on June 22, 2023. A questionnaire is a list of questions or items used to gather data from respondents about their attitudes, experiences, or opinions. Questionnaires can be used to collect quantitative and/or qualitative information. Questionnaires are commonly used in market research as well as in the social and health sciences.

  21. Becoming a Critical Reader: Questions to Ask About Quantitative Research

    Quantitative research seeks to prove something through experimentation and statistics. Once you've determined that what you have here is an original piece of quantitative research and you've already considered the basic questions here, you're ready for the specific questions:. 1.

  22. 8.3: Quantitative research questions

    Quantitative descriptive questions. The type of research you are conducting will impact the research question that you ask. Probably the easiest questions to think of are quantitative descriptive questions. For example, "What is the average student debt load of MSW students?" is a descriptive question—and an important one.

  23. Quantitative market research questions to ask for actionable insights

    Relationship-based questions for quantitative research. In quantitative research, especially when exploring relationship-based aspects, the key is not to cram multiple inquiries into one question but to ask them sequentially. This approach allows for a clearer and more focused response to each individual question.

  24. Daniella

    307 likes, 10 comments - montessoriandsensory on March 3, 2024: "As someone with a Doctorate and as a freelance education researcher, there are many things that I..."