quantitative research definition quizlet

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What is Quantitative Research? Definition, Methods, Types, and Examples

quantitative research definition quizlet

If you’re wondering what is quantitative research and whether this methodology works for your research study, you’re not alone. If you want a simple quantitative research definition , then it’s enough to say that this is a method undertaken by researchers based on their study requirements. However, to select the most appropriate research for their study type, researchers should know all the methods available. 

Selecting the right research method depends on a few important criteria, such as the research question, study type, time, costs, data availability, and availability of respondents. There are two main types of research methods— quantitative research  and qualitative research. The purpose of quantitative research is to validate or test a theory or hypothesis and that of qualitative research is to understand a subject or event or identify reasons for observed patterns. 

Quantitative research methods  are used to observe events that affect a particular group of individuals, which is the sample population. In this type of research, diverse numerical data are collected through various methods and then statistically analyzed to aggregate the data, compare them, or show relationships among the data. Quantitative research methods broadly include questionnaires, structured observations, and experiments.

Here are two quantitative research examples:

Satisfaction surveys sent out by a company regarding their revamped customer service initiatives. Customers are asked to rate their experience on a rating scale of 1 (poor) to 5 (excellent).
A school has introduced a new after-school program for children, and a few months after commencement, the school sends out feedback questionnaires to the parents of the enrolled children. Such questionnaires usually include close-ended questions that require either definite answers or a Yes/No option. This helps in a quick, overall assessment of the program’s outreach and success.

Table of Contents

What is quantitative research ? 1,2

The steps shown in the figure can be grouped into the following broad steps:

Theory : Define the problem area or area of interest and create a research question.
Hypothesis : Develop a hypothesis based on the research question. This hypothesis will be tested in the remaining steps.
Research design : In this step, the most appropriate quantitative research design will be selected, including deciding on the sample size, selecting respondents, identifying research sites, if any, etc.
Data collection : This process could be extensive based on your research objective and sample size.
Data analysis : Statistical analysis is used to analyze the data collected. The results from the analysis help in either supporting or rejecting your hypothesis.
Present results : Based on the data analysis, conclusions are drawn, and results are presented as accurately as possible.

Quantitative research characteristics 4

Large sample size : This ensures reliability because this sample represents the target population or market. Due to the large sample size, the outcomes can be generalized to the entire population as well, making this one of the important characteristics of quantitative research .
Structured data and measurable variables: The data are numeric and can be analyzed easily. Quantitative research involves the use of measurable variables such as age, salary range, highest education, etc.
Easy-to-use data collection methods : The methods include experiments, controlled observations, and questionnaires and surveys with a rating scale or close-ended questions, which require simple and to-the-point answers; are not bound by geographical regions; and are easy to administer.
Data analysis : Structured and accurate statistical analysis methods using software applications such as Excel, SPSS, R. The analysis is fast, accurate, and less effort intensive.
Reliable : The respondents answer close-ended questions, their responses are direct without ambiguity and yield numeric outcomes, which are therefore highly reliable.
Reusable outcomes : This is one of the key characteristics – outcomes of one research can be used and replicated in other research as well and is not exclusive to only one study.

Quantitative research methods 5

Quantitative research methods are classified into two types—primary and secondary.

Primary quantitative research method:

In this type of quantitative research , data are directly collected by the researchers using the following methods.

– Survey research : Surveys are the easiest and most commonly used quantitative research method . They are of two types— cross-sectional and longitudinal.

->Cross-sectional surveys are specifically conducted on a target population for a specified period, that is, these surveys have a specific starting and ending time and researchers study the events during this period to arrive at conclusions. The main purpose of these surveys is to describe and assess the characteristics of a population. There is one independent variable in this study, which is a common factor applicable to all participants in the population, for example, living in a specific city, diagnosed with a specific disease, of a certain age group, etc. An example of a cross-sectional survey is a study to understand why individuals residing in houses built before 1979 in the US are more susceptible to lead contamination.

->Longitudinal surveys are conducted at different time durations. These surveys involve observing the interactions among different variables in the target population, exposing them to various causal factors, and understanding their effects across a longer period. These studies are helpful to analyze a problem in the long term. An example of a longitudinal study is the study of the relationship between smoking and lung cancer over a long period.

– Descriptive research : Explains the current status of an identified and measurable variable. Unlike other types of quantitative research , a hypothesis is not needed at the beginning of the study and can be developed even after data collection. This type of quantitative research describes the characteristics of a problem and answers the what, when, where of a problem. However, it doesn’t answer the why of the problem and doesn’t explore cause-and-effect relationships between variables. Data from this research could be used as preliminary data for another study. Example: A researcher undertakes a study to examine the growth strategy of a company. This sample data can be used by other companies to determine their own growth strategy.

– Correlational research : This quantitative research method is used to establish a relationship between two variables using statistical analysis and analyze how one affects the other. The research is non-experimental because the researcher doesn’t control or manipulate any of the variables. At least two separate sample groups are needed for this research. Example: Researchers studying a correlation between regular exercise and diabetes.

– Causal-comparative research : This type of quantitative research examines the cause-effect relationships in retrospect between a dependent and independent variable and determines the causes of the already existing differences between groups of people. This is not a true experiment because it doesn’t assign participants to groups randomly. Example: To study the wage differences between men and women in the same role. For this, already existing wage information is analyzed to understand the relationship.

– Experimental research : This quantitative research method uses true experiments or scientific methods for determining a cause-effect relation between variables. It involves testing a hypothesis through experiments, in which one or more independent variables are manipulated and then their effect on dependent variables are studied. Example: A researcher studies the importance of a drug in treating a disease by administering the drug in few patients and not administering in a few.

The following data collection methods are commonly used in primary quantitative research :

Sampling : The most common type is probability sampling, in which a sample is chosen from a larger population using some form of random selection, that is, every member of the population has an equal chance of being selected. The different types of probability sampling are—simple random, systematic, stratified, and cluster sampling.
Interviews : These are commonly telephonic or face-to-face.
Observations : Structured observations are most commonly used in quantitative research . In this method, researchers make observations about specific behaviors of individuals in a structured setting.
Document review : Reviewing existing research or documents to collect evidence for supporting the quantitative research .
Surveys and questionnaires : Surveys can be administered both online and offline depending on the requirement and sample size.

The data collected can be analyzed in several ways in quantitative research , as listed below:

Cross-tabulation —Uses a tabular format to draw inferences among collected data
MaxDiff analysis —Gauges the preferences of the respondents
TURF analysis —Total Unduplicated Reach and Frequency Analysis; helps in determining the market strategy for a business
Gap analysis —Identify gaps in attaining the desired results
SWOT analysis —Helps identify strengths, weaknesses, opportunities, and threats of a product, service, or organization
Text analysis —Used for interpreting unstructured data

Secondary quantitative research methods :

This method involves conducting research using already existing or secondary data. This method is less effort intensive and requires lesser time. However, researchers should verify the authenticity and recency of the sources being used and ensure their accuracy.

The main sources of secondary data are:

The Internet
Government and non-government sources
Public libraries
Educational institutions
Commercial information sources such as newspapers, journals, radio, TV

When to use quantitative research 6

Here are some simple ways to decide when to use quantitative research . Use quantitative research to:

recommend a final course of action
find whether a consensus exists regarding a particular subject
generalize results to a larger population
determine a cause-and-effect relationship between variables
describe characteristics of specific groups of people
test hypotheses and examine specific relationships
identify and establish size of market segments

A research case study to understand when to use quantitative research 7

Context: A study was undertaken to evaluate a major innovation in a hospital’s design, in terms of workforce implications and impact on patient and staff experiences of all single-room hospital accommodations. The researchers undertook a mixed methods approach to answer their research questions. Here, we focus on the quantitative research aspect.

Research questions : What are the advantages and disadvantages for the staff as a result of the hospital’s move to the new design with all single-room accommodations? Did the move affect staff experience and well-being and improve their ability to deliver high-quality care?

Method: The researchers obtained quantitative data from three sources:

Staff activity (task time distribution): Each staff member was shadowed by a researcher who observed each task undertaken by the staff, and logged the time spent on each activity.
Staff travel distances : The staff were requested to wear pedometers, which recorded the distances covered.
Staff experience surveys : Staff were surveyed before and after the move to the new hospital design.

Results of quantitative research : The following observations were made based on quantitative data analysis:

The move to the new design did not result in a significant change in the proportion of time spent on different activities.
Staff activity events observed per session were higher after the move, and direct care and professional communication events per hour decreased significantly, suggesting fewer interruptions and less fragmented care.
A significant increase in medication tasks among the recorded events suggests that medication administration was integrated into patient care activities.
Travel distances increased for all staff, with highest increases for staff in the older people’s ward and surgical wards.
Ratings for staff toilet facilities, locker facilities, and space at staff bases were higher but those for social interaction and natural light were lower.

Advantages of quantitative research 1,2

When choosing the right research methodology, also consider the advantages of quantitative research and how it can impact your study.

Quantitative research methods are more scientific and rational. They use quantifiable data leading to objectivity in the results and avoid any chances of ambiguity.
This type of research uses numeric data so analysis is relatively easier .
In most cases, a hypothesis is already developed and quantitative research helps in testing and validatin g these constructed theories based on which researchers can make an informed decision about accepting or rejecting their theory.
The use of statistical analysis software ensures quick analysis of large volumes of data and is less effort intensive.
Higher levels of control can be applied to the research so the chances of bias can be reduced.
Quantitative research is based on measured value s, facts, and verifiable information so it can be easily checked or replicated by other researchers leading to continuity in scientific research.

Disadvantages of quantitative research 1,2

Quantitative research may also be limiting; take a look at the disadvantages of quantitative research.

Experiments are conducted in controlled settings instead of natural settings and it is possible for researchers to either intentionally or unintentionally manipulate the experiment settings to suit the results they desire.
Participants must necessarily give objective answers (either one- or two-word, or yes or no answers) and the reasons for their selection or the context are not considered.
Inadequate knowledge of statistical analysis methods may affect the results and their interpretation.
Although statistical analysis indicates the trends or patterns among variables, the reasons for these observed patterns cannot be interpreted and the research may not give a complete picture.
Large sample sizes are needed for more accurate and generalizable analysis .
Quantitative research cannot be used to address complex issues.

Frequently asked questions on  quantitative research  

Q:  What is the difference between quantitative research and qualitative research? 1

A:  The following table lists the key differences between quantitative research and qualitative research, some of which may have been mentioned earlier in the article.

Q:  What is the difference between reliability and validity? 8,9  

A:  The term reliability refers to the consistency of a research study. For instance, if a food-measuring weighing scale gives different readings every time the same quantity of food is measured then that weighing scale is not reliable. If the findings in a research study are consistent every time a measurement is made, then the study is considered reliable. However, it is usually unlikely to obtain the exact same results every time because some contributing variables may change. In such cases, a correlation coefficient is used to assess the degree of reliability. A strong positive correlation between the results indicates reliability.

Validity can be defined as the degree to which a tool actually measures what it claims to measure. It helps confirm the credibility of your research and suggests that the results may be generalizable. In other words, it measures the accuracy of the research.

The following table gives the key differences between reliability and validity.

Q:  What is mixed methods research? 10

A:  A mixed methods approach combines the characteristics of both quantitative research and qualitative research in the same study. This method allows researchers to validate their findings, verify if the results observed using both methods are complementary, and explain any unexpected results obtained from one method by using the other method. A mixed methods research design is useful in case of research questions that cannot be answered by either quantitative research or qualitative research alone. However, this method could be more effort- and cost-intensive because of the requirement of more resources. The figure 3 shows some basic mixed methods research designs that could be used.

Thus, quantitative research is the appropriate method for testing your hypotheses and can be used either alone or in combination with qualitative research per your study requirements. We hope this article has provided an insight into the various facets of quantitative research , including its different characteristics, advantages, and disadvantages, and a few tips to quickly understand when to use this research method.

References

Qualitative vs quantitative research: Differences, examples, & methods. Simply Psychology. Accessed Feb 28, 2023. https://simplypsychology.org/qualitative-quantitative.html#Quantitative-Research
Your ultimate guide to quantitative research. Qualtrics. Accessed February 28, 2023. https://www.qualtrics.com/uk/experience-management/research/quantitative-research/
The steps of quantitative research. Revise Sociology. Accessed March 1, 2023. https://revisesociology.com/2017/11/26/the-steps-of-quantitative-research/
What are the characteristics of quantitative research? Marketing91. Accessed March 1, 2023. https://www.marketing91.com/characteristics-of-quantitative-research/
Quantitative research: Types, characteristics, methods, & examples. ProProfs Survey Maker. Accessed February 28, 2023. https://www.proprofssurvey.com/blog/quantitative-research/#Characteristics_of_Quantitative_Research
Qualitative research isn’t as scientific as quantitative methods. Kmusial blog. Accessed March 5, 2023. https://kmusial.wordpress.com/2011/11/25/qualitative-research-isnt-as-scientific-as-quantitative-methods/
Maben J, Griffiths P, Penfold C, et al. Evaluating a major innovation in hospital design: workforce implications and impact on patient and staff experiences of all single room hospital accommodation. Southampton (UK): NIHR Journals Library; 2015 Feb. (Health Services and Delivery Research, No. 3.3.) Chapter 5, Case study quantitative data findings. Accessed March 6, 2023. https://www.ncbi.nlm.nih.gov/books/NBK274429/
McLeod, S. A. (2007).  What is reliability?  Simply Psychology. www.simplypsychology.org/reliability.html
Reliability vs validity: Differences & examples. Accessed March 5, 2023. https://statisticsbyjim.com/basics/reliability-vs-validity/
Mixed methods research. Community Engagement Program. Harvard Catalyst. Accessed February 28, 2023. https://catalyst.harvard.edu/community-engagement/mmr

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Home » Quantitative Research – Methods, Types and Analysis

Quantitative Research – Methods, Types and Analysis

Table of Contents

Quantitative Research

Quantitative research is a type of research that collects and analyzes numerical data to test hypotheses and answer research questions . This research typically involves a large sample size and uses statistical analysis to make inferences about a population based on the data collected. It often involves the use of surveys, experiments, or other structured data collection methods to gather quantitative data.

Quantitative Research Methods

Quantitative Research Methods are as follows:

Descriptive Research Design

Descriptive research design is used to describe the characteristics of a population or phenomenon being studied. This research method is used to answer the questions of what, where, when, and how. Descriptive research designs use a variety of methods such as observation, case studies, and surveys to collect data. The data is then analyzed using statistical tools to identify patterns and relationships.

Correlational Research Design

Correlational research design is used to investigate the relationship between two or more variables. Researchers use correlational research to determine whether a relationship exists between variables and to what extent they are related. This research method involves collecting data from a sample and analyzing it using statistical tools such as correlation coefficients.

Quasi-experimental Research Design

Quasi-experimental research design is used to investigate cause-and-effect relationships between variables. This research method is similar to experimental research design, but it lacks full control over the independent variable. Researchers use quasi-experimental research designs when it is not feasible or ethical to manipulate the independent variable.

Experimental Research Design

Experimental research design is used to investigate cause-and-effect relationships between variables. This research method involves manipulating the independent variable and observing the effects on the dependent variable. Researchers use experimental research designs to test hypotheses and establish cause-and-effect relationships.

Survey Research

Survey research involves collecting data from a sample of individuals using a standardized questionnaire. This research method is used to gather information on attitudes, beliefs, and behaviors of individuals. Researchers use survey research to collect data quickly and efficiently from a large sample size. Survey research can be conducted through various methods such as online, phone, mail, or in-person interviews.

Quantitative Research Analysis Methods

Here are some commonly used quantitative research analysis methods:

Statistical Analysis

Statistical analysis is the most common quantitative research analysis method. It involves using statistical tools and techniques to analyze the numerical data collected during the research process. Statistical analysis can be used to identify patterns, trends, and relationships between variables, and to test hypotheses and theories.

Regression Analysis

Regression analysis is a statistical technique used to analyze the relationship between one dependent variable and one or more independent variables. Researchers use regression analysis to identify and quantify the impact of independent variables on the dependent variable.

Factor Analysis

Factor analysis is a statistical technique used to identify underlying factors that explain the correlations among a set of variables. Researchers use factor analysis to reduce a large number of variables to a smaller set of factors that capture the most important information.

Structural Equation Modeling

Structural equation modeling is a statistical technique used to test complex relationships between variables. It involves specifying a model that includes both observed and unobserved variables, and then using statistical methods to test the fit of the model to the data.

Time Series Analysis

Time series analysis is a statistical technique used to analyze data that is collected over time. It involves identifying patterns and trends in the data, as well as any seasonal or cyclical variations.

Multilevel Modeling

Multilevel modeling is a statistical technique used to analyze data that is nested within multiple levels. For example, researchers might use multilevel modeling to analyze data that is collected from individuals who are nested within groups, such as students nested within schools.

Applications of Quantitative Research

Quantitative research has many applications across a wide range of fields. Here are some common examples:

Market Research : Quantitative research is used extensively in market research to understand consumer behavior, preferences, and trends. Researchers use surveys, experiments, and other quantitative methods to collect data that can inform marketing strategies, product development, and pricing decisions.
Health Research: Quantitative research is used in health research to study the effectiveness of medical treatments, identify risk factors for diseases, and track health outcomes over time. Researchers use statistical methods to analyze data from clinical trials, surveys, and other sources to inform medical practice and policy.
Social Science Research: Quantitative research is used in social science research to study human behavior, attitudes, and social structures. Researchers use surveys, experiments, and other quantitative methods to collect data that can inform social policies, educational programs, and community interventions.
Education Research: Quantitative research is used in education research to study the effectiveness of teaching methods, assess student learning outcomes, and identify factors that influence student success. Researchers use experimental and quasi-experimental designs, as well as surveys and other quantitative methods, to collect and analyze data.
Environmental Research: Quantitative research is used in environmental research to study the impact of human activities on the environment, assess the effectiveness of conservation strategies, and identify ways to reduce environmental risks. Researchers use statistical methods to analyze data from field studies, experiments, and other sources.

Characteristics of Quantitative Research

Here are some key characteristics of quantitative research:

Numerical data : Quantitative research involves collecting numerical data through standardized methods such as surveys, experiments, and observational studies. This data is analyzed using statistical methods to identify patterns and relationships.
Large sample size: Quantitative research often involves collecting data from a large sample of individuals or groups in order to increase the reliability and generalizability of the findings.
Objective approach: Quantitative research aims to be objective and impartial in its approach, focusing on the collection and analysis of data rather than personal beliefs, opinions, or experiences.
Control over variables: Quantitative research often involves manipulating variables to test hypotheses and establish cause-and-effect relationships. Researchers aim to control for extraneous variables that may impact the results.
Replicable : Quantitative research aims to be replicable, meaning that other researchers should be able to conduct similar studies and obtain similar results using the same methods.
Statistical analysis: Quantitative research involves using statistical tools and techniques to analyze the numerical data collected during the research process. Statistical analysis allows researchers to identify patterns, trends, and relationships between variables, and to test hypotheses and theories.
Generalizability: Quantitative research aims to produce findings that can be generalized to larger populations beyond the specific sample studied. This is achieved through the use of random sampling methods and statistical inference.

Examples of Quantitative Research

Here are some examples of quantitative research in different fields:

Market Research: A company conducts a survey of 1000 consumers to determine their brand awareness and preferences. The data is analyzed using statistical methods to identify trends and patterns that can inform marketing strategies.
Health Research : A researcher conducts a randomized controlled trial to test the effectiveness of a new drug for treating a particular medical condition. The study involves collecting data from a large sample of patients and analyzing the results using statistical methods.
Social Science Research : A sociologist conducts a survey of 500 people to study attitudes toward immigration in a particular country. The data is analyzed using statistical methods to identify factors that influence these attitudes.
Education Research: A researcher conducts an experiment to compare the effectiveness of two different teaching methods for improving student learning outcomes. The study involves randomly assigning students to different groups and collecting data on their performance on standardized tests.
Environmental Research : A team of researchers conduct a study to investigate the impact of climate change on the distribution and abundance of a particular species of plant or animal. The study involves collecting data on environmental factors and population sizes over time and analyzing the results using statistical methods.
Psychology : A researcher conducts a survey of 500 college students to investigate the relationship between social media use and mental health. The data is analyzed using statistical methods to identify correlations and potential causal relationships.
Political Science: A team of researchers conducts a study to investigate voter behavior during an election. They use survey methods to collect data on voting patterns, demographics, and political attitudes, and analyze the results using statistical methods.

How to Conduct Quantitative Research

Here is a general overview of how to conduct quantitative research:

Develop a research question: The first step in conducting quantitative research is to develop a clear and specific research question. This question should be based on a gap in existing knowledge, and should be answerable using quantitative methods.
Develop a research design: Once you have a research question, you will need to develop a research design. This involves deciding on the appropriate methods to collect data, such as surveys, experiments, or observational studies. You will also need to determine the appropriate sample size, data collection instruments, and data analysis techniques.
Collect data: The next step is to collect data. This may involve administering surveys or questionnaires, conducting experiments, or gathering data from existing sources. It is important to use standardized methods to ensure that the data is reliable and valid.
Analyze data : Once the data has been collected, it is time to analyze it. This involves using statistical methods to identify patterns, trends, and relationships between variables. Common statistical techniques include correlation analysis, regression analysis, and hypothesis testing.
Interpret results: After analyzing the data, you will need to interpret the results. This involves identifying the key findings, determining their significance, and drawing conclusions based on the data.
Communicate findings: Finally, you will need to communicate your findings. This may involve writing a research report, presenting at a conference, or publishing in a peer-reviewed journal. It is important to clearly communicate the research question, methods, results, and conclusions to ensure that others can understand and replicate your research.

When to use Quantitative Research

Here are some situations when quantitative research can be appropriate:

To test a hypothesis: Quantitative research is often used to test a hypothesis or a theory. It involves collecting numerical data and using statistical analysis to determine if the data supports or refutes the hypothesis.
To generalize findings: If you want to generalize the findings of your study to a larger population, quantitative research can be useful. This is because it allows you to collect numerical data from a representative sample of the population and use statistical analysis to make inferences about the population as a whole.
To measure relationships between variables: If you want to measure the relationship between two or more variables, such as the relationship between age and income, or between education level and job satisfaction, quantitative research can be useful. It allows you to collect numerical data on both variables and use statistical analysis to determine the strength and direction of the relationship.
To identify patterns or trends: Quantitative research can be useful for identifying patterns or trends in data. For example, you can use quantitative research to identify trends in consumer behavior or to identify patterns in stock market data.
To quantify attitudes or opinions : If you want to measure attitudes or opinions on a particular topic, quantitative research can be useful. It allows you to collect numerical data using surveys or questionnaires and analyze the data using statistical methods to determine the prevalence of certain attitudes or opinions.

Purpose of Quantitative Research

The purpose of quantitative research is to systematically investigate and measure the relationships between variables or phenomena using numerical data and statistical analysis. The main objectives of quantitative research include:

Description : To provide a detailed and accurate description of a particular phenomenon or population.
Explanation : To explain the reasons for the occurrence of a particular phenomenon, such as identifying the factors that influence a behavior or attitude.
Prediction : To predict future trends or behaviors based on past patterns and relationships between variables.
Control : To identify the best strategies for controlling or influencing a particular outcome or behavior.

Quantitative research is used in many different fields, including social sciences, business, engineering, and health sciences. It can be used to investigate a wide range of phenomena, from human behavior and attitudes to physical and biological processes. The purpose of quantitative research is to provide reliable and valid data that can be used to inform decision-making and improve understanding of the world around us.

Advantages of Quantitative Research

There are several advantages of quantitative research, including:

Objectivity : Quantitative research is based on objective data and statistical analysis, which reduces the potential for bias or subjectivity in the research process.
Reproducibility : Because quantitative research involves standardized methods and measurements, it is more likely to be reproducible and reliable.
Generalizability : Quantitative research allows for generalizations to be made about a population based on a representative sample, which can inform decision-making and policy development.
Precision : Quantitative research allows for precise measurement and analysis of data, which can provide a more accurate understanding of phenomena and relationships between variables.
Efficiency : Quantitative research can be conducted relatively quickly and efficiently, especially when compared to qualitative research, which may involve lengthy data collection and analysis.
Large sample sizes : Quantitative research can accommodate large sample sizes, which can increase the representativeness and generalizability of the results.

Limitations of Quantitative Research

There are several limitations of quantitative research, including:

Limited understanding of context: Quantitative research typically focuses on numerical data and statistical analysis, which may not provide a comprehensive understanding of the context or underlying factors that influence a phenomenon.
Simplification of complex phenomena: Quantitative research often involves simplifying complex phenomena into measurable variables, which may not capture the full complexity of the phenomenon being studied.
Potential for researcher bias: Although quantitative research aims to be objective, there is still the potential for researcher bias in areas such as sampling, data collection, and data analysis.
Limited ability to explore new ideas: Quantitative research is often based on pre-determined research questions and hypotheses, which may limit the ability to explore new ideas or unexpected findings.
Limited ability to capture subjective experiences : Quantitative research is typically focused on objective data and may not capture the subjective experiences of individuals or groups being studied.
Ethical concerns : Quantitative research may raise ethical concerns, such as invasion of privacy or the potential for harm to participants.

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What Is Quantitative Research? | Definition & Methods

What Is Quantitative Research? | Definition & Methods

Published on 4 April 2022 by Pritha Bhandari . Revised on 10 October 2022.

Quantitative research is the process of collecting and analysing numerical data. It can be used to find patterns and averages, make predictions, test causal relationships, and generalise results to wider populations.

Quantitative research is the opposite of qualitative research , which involves collecting and analysing non-numerical data (e.g. text, video, or audio).

Quantitative research is widely used in the natural and social sciences: biology, chemistry, psychology, economics, sociology, marketing, etc.

What is the demographic makeup of Singapore in 2020?
How has the average temperature changed globally over the last century?
Does environmental pollution affect the prevalence of honey bees?
Does working from home increase productivity for people with long commutes?

Quantitative research methods, quantitative data analysis, advantages of quantitative research, disadvantages of quantitative research, frequently asked questions about quantitative research.

You can use quantitative research methods for descriptive, correlational or experimental research.

In descriptive research , you simply seek an overall summary of your study variables.
In correlational research , you investigate relationships between your study variables.
In experimental research , you systematically examine whether there is a cause-and-effect relationship between variables.

Correlational and experimental research can both be used to formally test hypotheses , or predictions, using statistics. The results may be generalised to broader populations based on the sampling method used.

To collect quantitative data, you will often need to use operational definitions that translate abstract concepts (e.g., mood) into observable and quantifiable measures (e.g., self-ratings of feelings and energy levels).

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Once data is collected, you may need to process it before it can be analysed. For example, survey and test data may need to be transformed from words to numbers. Then, you can use statistical analysis to answer your research questions .

Descriptive statistics will give you a summary of your data and include measures of averages and variability. You can also use graphs, scatter plots and frequency tables to visualise your data and check for any trends or outliers.

Using inferential statistics , you can make predictions or generalisations based on your data. You can test your hypothesis or use your sample data to estimate the population parameter .

You can also assess the reliability and validity of your data collection methods to indicate how consistently and accurately your methods actually measured what you wanted them to.

Quantitative research is often used to standardise data collection and generalise findings . Strengths of this approach include:

Replication

Repeating the study is possible because of standardised data collection protocols and tangible definitions of abstract concepts.

Direct comparisons of results

The study can be reproduced in other cultural settings, times or with different groups of participants. Results can be compared statistically.

Large samples

Data from large samples can be processed and analysed using reliable and consistent procedures through quantitative data analysis.

Hypothesis testing

Using formalised and established hypothesis testing procedures means that you have to carefully consider and report your research variables, predictions, data collection and testing methods before coming to a conclusion.

Despite the benefits of quantitative research, it is sometimes inadequate in explaining complex research topics. Its limitations include:

Superficiality

Using precise and restrictive operational definitions may inadequately represent complex concepts. For example, the concept of mood may be represented with just a number in quantitative research, but explained with elaboration in qualitative research.

Narrow focus

Predetermined variables and measurement procedures can mean that you ignore other relevant observations.

Structural bias

Despite standardised procedures, structural biases can still affect quantitative research. Missing data , imprecise measurements or inappropriate sampling methods are biases that can lead to the wrong conclusions.

Lack of context

Quantitative research often uses unnatural settings like laboratories or fails to consider historical and cultural contexts that may affect data collection and results.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organisations.

Operationalisation means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioural avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalise the variables that you want to measure.

Reliability and validity are both about how well a method measures something:

Reliability refers to the consistency of a measure (whether the results can be reproduced under the same conditions).
Validity refers to the accuracy of a measure (whether the results really do represent what they are supposed to measure).

If you are doing experimental research , you also have to consider the internal and external validity of your experiment.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

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Quantitative and Qualitative Research

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What is Quantitative Research?

What is Qualitative Research?
Quantitative vs Qualitative
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Quantitative methodology is the dominant research framework in the social sciences. It refers to a set of strategies, techniques and assumptions used to study psychological, social and economic processes through the exploration of numeric patterns . Quantitative research gathers a range of numeric data. Some of the numeric data is intrinsically quantitative (e.g. personal income), while in other cases the numeric structure is imposed (e.g. ‘On a scale from 1 to 10, how depressed did you feel last week?’). The collection of quantitative information allows researchers to conduct simple to extremely sophisticated statistical analyses that aggregate the data (e.g. averages, percentages), show relationships among the data (e.g. ‘Students with lower grade point averages tend to score lower on a depression scale’) or compare across aggregated data (e.g. the USA has a higher gross domestic product than Spain). Quantitative research includes methodologies such as questionnaires, structured observations or experiments and stands in contrast to qualitative research. Qualitative research involves the collection and analysis of narratives and/or open-ended observations through methodologies such as interviews, focus groups or ethnographies.

Coghlan, D., Brydon-Miller, M. (2014). The SAGE encyclopedia of action research (Vols. 1-2). London, : SAGE Publications Ltd doi: 10.4135/9781446294406

What is the purpose of quantitative research?

The purpose of quantitative research is to generate knowledge and create understanding about the social world. Quantitative research is used by social scientists, including communication researchers, to observe phenomena or occurrences affecting individuals. Social scientists are concerned with the study of people. Quantitative research is a way to learn about a particular group of people, known as a sample population. Using scientific inquiry, quantitative research relies on data that are observed or measured to examine questions about the sample population.

Allen, M. (2017). The SAGE encyclopedia of communication research methods (Vols. 1-4). Thousand Oaks, CA: SAGE Publications, Inc doi: 10.4135/9781483381411

How do I know if the study is a quantitative design? What type of quantitative study is it?

Quantitative Research Designs: Descriptive non-experimental, Quasi-experimental or Experimental?

Studies do not always explicitly state what kind of research design is being used. You will need to know how to decipher which design type is used. The following video will help you determine the quantitative design type.

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Quantitative Research in the Social Sciences

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Quantitative methods emphasize objective measurements and the statistical, mathematical, or numerical analysis of data collected through polls, questionnaires, and surveys, or by manipulating pre-existing statistical data using computational techniques . Quantitative research focuses on gathering numerical data and generalizing it across groups of people or to explain a particular phenomenon.

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Muijs, Daniel. Doing Quantitative Research in Education with SPSS . 2nd edition. London: SAGE Publications, 2010.

Characteristics of Quantitative Research

Your goal in conducting quantitative research study is to determine the relationship between one thing [an independent variable] and another [a dependent or outcome variable] within a population. Quantitative research designs are either descriptive [subjects usually measured once] or experimental [subjects measured before and after a treatment]. A descriptive study establishes only associations between variables; an experimental study establishes causality.

Quantitative research deals in numbers, logic, and an objective stance. Quantitative research focuses on numberic and unchanging data and detailed, convergent reasoning rather than divergent reasoning [i.e., the generation of a variety of ideas about a research problem in a spontaneous, free-flowing manner].

Its main characteristics are :

The data is usually gathered using structured research instruments.
The results are based on larger sample sizes that are representative of the population.
The research study can usually be replicated or repeated, given its high reliability.
Researcher has a clearly defined research question to which objective answers are sought.
All aspects of the study are carefully designed before data is collected.
Data are in the form of numbers and statistics, often arranged in tables, charts, figures, or other non-textual forms.
Project can be used to generalize concepts more widely, predict future results, or investigate causal relationships.
Researcher uses tools, such as questionnaires or computer software, to collect numerical data.

The overarching aim of a quantitative research study is to classify features, count them, and construct statistical models in an attempt to explain what is observed.

Things to keep in mind when reporting the results of a study using quantiative methods :

Explain the data collected and their statistical treatment as well as all relevant results in relation to the research problem you are investigating. Interpretation of results is not appropriate in this section.
Report unanticipated events that occurred during your data collection. Explain how the actual analysis differs from the planned analysis. Explain your handling of missing data and why any missing data does not undermine the validity of your analysis.
Explain the techniques you used to "clean" your data set.
Choose a minimally sufficient statistical procedure ; provide a rationale for its use and a reference for it. Specify any computer programs used.
Describe the assumptions for each procedure and the steps you took to ensure that they were not violated.
When using inferential statistics , provide the descriptive statistics, confidence intervals, and sample sizes for each variable as well as the value of the test statistic, its direction, the degrees of freedom, and the significance level [report the actual p value].
Avoid inferring causality , particularly in nonrandomized designs or without further experimentation.
Use tables to provide exact values ; use figures to convey global effects. Keep figures small in size; include graphic representations of confidence intervals whenever possible.
Always tell the reader what to look for in tables and figures .

NOTE: When using pre-existing statistical data gathered and made available by anyone other than yourself [e.g., government agency], you still must report on the methods that were used to gather the data and describe any missing data that exists and, if there is any, provide a clear explanation why the missing datat does not undermine the validity of your final analysis.

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Brians, Craig Leonard et al. Empirical Political Analysis: Quantitative and Qualitative Research Methods . 8th ed. Boston, MA: Longman, 2011; McNabb, David E. Research Methods in Public Administration and Nonprofit Management: Quantitative and Qualitative Approaches . 2nd ed. Armonk, NY: M.E. Sharpe, 2008; Quantitative Research Methods . Writing@CSU. Colorado State University; Singh, Kultar. Quantitative Social Research Methods . Los Angeles, CA: Sage, 2007.

Basic Research Designs for Quantitative Studies

Before designing a quantitative research study, you must decide whether it will be descriptive or experimental because this will dictate how you gather, analyze, and interpret the results. A descriptive study is governed by the following rules: subjects are generally measured once; the intention is to only establish associations between variables; and, the study may include a sample population of hundreds or thousands of subjects to ensure that a valid estimate of a generalized relationship between variables has been obtained. An experimental design includes subjects measured before and after a particular treatment, the sample population may be very small and purposefully chosen, and it is intended to establish causality between variables. Introduction The introduction to a quantitative study is usually written in the present tense and from the third person point of view. It covers the following information:

Identifies the research problem -- as with any academic study, you must state clearly and concisely the research problem being investigated.
Reviews the literature -- review scholarship on the topic, synthesizing key themes and, if necessary, noting studies that have used similar methods of inquiry and analysis. Note where key gaps exist and how your study helps to fill these gaps or clarifies existing knowledge.
Describes the theoretical framework -- provide an outline of the theory or hypothesis underpinning your study. If necessary, define unfamiliar or complex terms, concepts, or ideas and provide the appropriate background information to place the research problem in proper context [e.g., historical, cultural, economic, etc.].

Methodology The methods section of a quantitative study should describe how each objective of your study will be achieved. Be sure to provide enough detail to enable the reader can make an informed assessment of the methods being used to obtain results associated with the research problem. The methods section should be presented in the past tense.

Study population and sampling -- where did the data come from; how robust is it; note where gaps exist or what was excluded. Note the procedures used for their selection;
Data collection – describe the tools and methods used to collect information and identify the variables being measured; describe the methods used to obtain the data; and, note if the data was pre-existing [i.e., government data] or you gathered it yourself. If you gathered it yourself, describe what type of instrument you used and why. Note that no data set is perfect--describe any limitations in methods of gathering data.
Data analysis -- describe the procedures for processing and analyzing the data. If appropriate, describe the specific instruments of analysis used to study each research objective, including mathematical techniques and the type of computer software used to manipulate the data.

Results The finding of your study should be written objectively and in a succinct and precise format. In quantitative studies, it is common to use graphs, tables, charts, and other non-textual elements to help the reader understand the data. Make sure that non-textual elements do not stand in isolation from the text but are being used to supplement the overall description of the results and to help clarify key points being made. Further information about how to effectively present data using charts and graphs can be found here .

Statistical analysis -- how did you analyze the data? What were the key findings from the data? The findings should be present in a logical, sequential order. Describe but do not interpret these trends or negative results; save that for the discussion section. The results should be presented in the past tense.

Discussion Discussions should be analytic, logical, and comprehensive. The discussion should meld together your findings in relation to those identified in the literature review, and placed within the context of the theoretical framework underpinning the study. The discussion should be presented in the present tense.

Interpretation of results -- reiterate the research problem being investigated and compare and contrast the findings with the research questions underlying the study. Did they affirm predicted outcomes or did the data refute it?
Description of trends, comparison of groups, or relationships among variables -- describe any trends that emerged from your analysis and explain all unanticipated and statistical insignificant findings.
Discussion of implications – what is the meaning of your results? Highlight key findings based on the overall results and note findings that you believe are important. How have the results helped fill gaps in understanding the research problem?
Limitations -- describe any limitations or unavoidable bias in your study and, if necessary, note why these limitations did not inhibit effective interpretation of the results.

Conclusion End your study by to summarizing the topic and provide a final comment and assessment of the study.

Summary of findings – synthesize the answers to your research questions. Do not report any statistical data here; just provide a narrative summary of the key findings and describe what was learned that you did not know before conducting the study.
Recommendations – if appropriate to the aim of the assignment, tie key findings with policy recommendations or actions to be taken in practice.
Future research – note the need for future research linked to your study’s limitations or to any remaining gaps in the literature that were not addressed in your study.

Black, Thomas R. Doing Quantitative Research in the Social Sciences: An Integrated Approach to Research Design, Measurement and Statistics . London: Sage, 1999; Gay,L. R. and Peter Airasain. Educational Research: Competencies for Analysis and Applications . 7th edition. Upper Saddle River, NJ: Merril Prentice Hall, 2003; Hector, Anestine. An Overview of Quantitative Research in Compostion and TESOL . Department of English, Indiana University of Pennsylvania; Hopkins, Will G. “Quantitative Research Design.” Sportscience 4, 1 (2000); A Strategy for Writing Up Research Results . The Structure, Format, Content, and Style of a Journal-Style Scientific Paper. Department of Biology. Bates College; Nenty, H. Johnson. "Writing a Quantitative Research Thesis." International Journal of Educational Science 1 (2009): 19-32; Ouyang, Ronghua (John). Basic Inquiry of Quantitative Research . Kennesaw State University.

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Characteristics of Quantitative Research

Quantitative research deals in numbers, logic, and an objective stance. Quantitative research focuses on numeric and unchanging data and detailed, convergent reasoning rather than divergent reasoning [i.e., the generation of a variety of ideas about a research problem in a spontaneous, free-flowing manner].

Its main characteristics are :

The data is usually gathered using structured research instruments.
The results are based on larger sample sizes that are representative of the population.
The research study can usually be replicated or repeated, given its high reliability.
Researcher has a clearly defined research question to which objective answers are sought.
All aspects of the study are carefully designed before data is collected.
Data are in the form of numbers and statistics, often arranged in tables, charts, figures, or other non-textual forms.
Project can be used to generalize concepts more widely, predict future results, or investigate causal relationships.
Researcher uses tools, such as questionnaires or computer software, to collect numerical data.

The overarching aim of a quantitative research study is to classify features, count them, and construct statistical models in an attempt to explain what is observed.

Things to keep in mind when reporting the results of a study using quantitative methods :

Explain the data collected and their statistical treatment as well as all relevant results in relation to the research problem you are investigating. Interpretation of results is not appropriate in this section.
Report unanticipated events that occurred during your data collection. Explain how the actual analysis differs from the planned analysis. Explain your handling of missing data and why any missing data does not undermine the validity of your analysis.
Explain the techniques you used to "clean" your data set.
Choose a minimally sufficient statistical procedure ; provide a rationale for its use and a reference for it. Specify any computer programs used.
Describe the assumptions for each procedure and the steps you took to ensure that they were not violated.
When using inferential statistics , provide the descriptive statistics, confidence intervals, and sample sizes for each variable as well as the value of the test statistic, its direction, the degrees of freedom, and the significance level [report the actual p value].
Avoid inferring causality , particularly in nonrandomized designs or without further experimentation.
Use tables to provide exact values ; use figures to convey global effects. Keep figures small in size; include graphic representations of confidence intervals whenever possible.
Always tell the reader what to look for in tables and figures .

NOTE: When using pre-existing statistical data gathered and made available by anyone other than yourself [e.g., government agency], you still must report on the methods that were used to gather the data and describe any missing data that exists and, if there is any, provide a clear explanation why the missing data does not undermine the validity of your final analysis.

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Brians, Craig Leonard et al. Empirical Political Analysis: Quantitative and Qualitative Research Methods . 8th ed. Boston, MA: Longman, 2011; McNabb, David E. Research Methods in Public Administration and Nonprofit Management: Quantitative and Qualitative Approaches . 2nd ed. Armonk, NY: M.E. Sharpe, 2008; Quantitative Research Methods. Writing@CSU. Colorado State University; Singh, Kultar. Quantitative Social Research Methods . Los Angeles, CA: Sage, 2007.

Basic Research Design for Quantitative Studies

Identifies the research problem -- as with any academic study, you must state clearly and concisely the research problem being investigated.
Reviews the literature -- review scholarship on the topic, synthesizing key themes and, if necessary, noting studies that have used similar methods of inquiry and analysis. Note where key gaps exist and how your study helps to fill these gaps or clarifies existing knowledge.
Describes the theoretical framework -- provide an outline of the theory or hypothesis underpinning your study. If necessary, define unfamiliar or complex terms, concepts, or ideas and provide the appropriate background information to place the research problem in proper context [e.g., historical, cultural, economic, etc.].

Study population and sampling -- where did the data come from; how robust is it; note where gaps exist or what was excluded. Note the procedures used for their selection;
Data collection – describe the tools and methods used to collect information and identify the variables being measured; describe the methods used to obtain the data; and, note if the data was pre-existing [i.e., government data] or you gathered it yourself. If you gathered it yourself, describe what type of instrument you used and why. Note that no data set is perfect--describe any limitations in methods of gathering data.
Data analysis -- describe the procedures for processing and analyzing the data. If appropriate, describe the specific instruments of analysis used to study each research objective, including mathematical techniques and the type of computer software used to manipulate the data.

Statistical analysis -- how did you analyze the data? What were the key findings from the data? The findings should be present in a logical, sequential order. Describe but do not interpret these trends or negative results; save that for the discussion section. The results should be presented in the past tense.

Interpretation of results -- reiterate the research problem being investigated and compare and contrast the findings with the research questions underlying the study. Did they affirm predicted outcomes or did the data refute it?
Description of trends, comparison of groups, or relationships among variables -- describe any trends that emerged from your analysis and explain all unanticipated and statistical insignificant findings.
Discussion of implications – what is the meaning of your results? Highlight key findings based on the overall results and note findings that you believe are important. How have the results helped fill gaps in understanding the research problem?
Limitations -- describe any limitations or unavoidable bias in your study and, if necessary, note why these limitations did not inhibit effective interpretation of the results.

Conclusion End your study by to summarizing the topic and provide a final comment and assessment of the study.

Summary of findings – synthesize the answers to your research questions. Do not report any statistical data here; just provide a narrative summary of the key findings and describe what was learned that you did not know before conducting the study.
Recommendations – if appropriate to the aim of the assignment, tie key findings with policy recommendations or actions to be taken in practice.
Future research – note the need for future research linked to your study’s limitations or to any remaining gaps in the literature that were not addressed in your study.

Black, Thomas R. Doing Quantitative Research in the Social Sciences: An Integrated Approach to Research Design, Measurement and Statistics . London: Sage, 1999; Gay,L. R. and Peter Airasain. Educational Research: Competencies for Analysis and Applications . 7th edition. Upper Saddle River, NJ: Merril Prentice Hall, 2003; Hector, Anestine. An Overview of Quantitative Research in Composition and TESOL . Department of English, Indiana University of Pennsylvania; Hopkins, Will G. “Quantitative Research Design.” Sportscience 4, 1 (2000); "A Strategy for Writing Up Research Results. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper." Department of Biology. Bates College; Nenty, H. Johnson. "Writing a Quantitative Research Thesis." International Journal of Educational Science 1 (2009): 19-32; Ouyang, Ronghua (John). Basic Inquiry of Quantitative Research . Kennesaw State University.

Strengths of Using Quantitative Methods

Quantitative researchers try to recognize and isolate specific variables contained within the study framework, seek correlation, relationships and causality, and attempt to control the environment in which the data is collected to avoid the risk of variables, other than the one being studied, accounting for the relationships identified.

Among the specific strengths of using quantitative methods to study social science research problems:

Allows for a broader study, involving a greater number of subjects, and enhancing the generalization of the results;
Allows for greater objectivity and accuracy of results. Generally, quantitative methods are designed to provide summaries of data that support generalizations about the phenomenon under study. In order to accomplish this, quantitative research usually involves few variables and many cases, and employs prescribed procedures to ensure validity and reliability;
Applying well established standards means that the research can be replicated, and then analyzed and compared with similar studies;
You can summarize vast sources of information and make comparisons across categories and over time; and,
Personal bias can be avoided by keeping a 'distance' from participating subjects and using accepted computational techniques .

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Brians, Craig Leonard et al. Empirical Political Analysis: Quantitative and Qualitative Research Methods . 8th ed. Boston, MA: Longman, 2011; McNabb, David E. Research Methods in Public Administration and Nonprofit Management: Quantitative and Qualitative Approaches . 2nd ed. Armonk, NY: M.E. Sharpe, 2008; Singh, Kultar. Quantitative Social Research Methods . Los Angeles, CA: Sage, 2007.

Limitations of Using Quantitative Methods

Quantitative methods presume to have an objective approach to studying research problems, where data is controlled and measured, to address the accumulation of facts, and to determine the causes of behavior. As a consequence, the results of quantitative research may be statistically significant but are often humanly insignificant.

Some specific limitations associated with using quantitative methods to study research problems in the social sciences include:

Quantitative data is more efficient and able to test hypotheses, but may miss contextual detail;
Uses a static and rigid approach and so employs an inflexible process of discovery;
The development of standard questions by researchers can lead to "structural bias" and false representation, where the data actually reflects the view of the researcher instead of the participating subject;
Results provide less detail on behavior, attitudes, and motivation;
Researcher may collect a much narrower and sometimes superficial dataset;
Results are limited as they provide numerical descriptions rather than detailed narrative and generally provide less elaborate accounts of human perception;
The research is often carried out in an unnatural, artificial environment so that a level of control can be applied to the exercise. This level of control might not normally be in place in the real world thus yielding "laboratory results" as opposed to "real world results"; and,
Preset answers will not necessarily reflect how people really feel about a subject and, in some cases, might just be the closest match to the preconceived hypothesis.

Research Tip

Finding Examples of How to Apply Different Types of Research Methods

SAGE publications is a major publisher of studies about how to design and conduct research in the social and behavioral sciences. Their SAGE Research Methods Online and Cases database includes contents from books, articles, encyclopedias, handbooks, and videos covering social science research design and methods including the complete Little Green Book Series of Quantitative Applications in the Social Sciences and the Little Blue Book Series of Qualitative Research techniques. The database also includes case studies outlining the research methods used in real research projects. This is an excellent source for finding definitions of key terms and descriptions of research design and practice, techniques of data gathering, analysis, and reporting, and information about theories of research [e.g., grounded theory]. The database covers both qualitative and quantitative research methods as well as mixed methods approaches to conducting research.

SAGE Research Methods Online and Cases

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Quantitative and Qualitative Research Methods

First Online: 03 January 2022

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Andrew England 5

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Quantitative research uses methods that seek to explain phenomena by collecting numerical data, which are then analysed mathematically, typically by statistics. With quantitative approaches, the data produced are always numerical; if there are no numbers, then the methods are not quantitative. Many phenomena lend themselves to quantitative methods because the relevant information is already available numerically. Qualitative methods provide a mechanism to provide answers based on the collection of non-numerical data ‘i.e words, actions, behaviours’. Both quantitative and qualitative methodologies are important in medical imaging and radiation therapy. In some instances, both quantitative and qualitative approaches can be combined into a mixed-methods approach. This chapter discusses all methodological approaches to research from both medical imaging and radiation therapy perspectives.

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England, A. (2021). Quantitative and Qualitative Research Methods. In: Seeram, E., Davidson, R., England, A., McEntee, M.F. (eds) Research for Medical Imaging and Radiation Sciences. Springer, Cham. https://doi.org/10.1007/978-3-030-79956-4_5

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StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

StatPearls [Internet].

Human subjects research design.

Marlon L. Bayot ; Grace D. Brannan ; Janelle M. Brannan ; Steven Tenny .

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Last Update: August 14, 2023 .

Definition/Introduction

Human subjects research is a heavily regulated type of research, hence this paper will start with two critical definitions. The US Department of Health and Human Services (HHS) Code of Federal Regulations, 45 CFR 46, provides the following definitions: [1] “A living individual about whom an investigator (whether professional or student) conducting research:

Obtains information or biospecimens through intervention or interaction with the individual, and uses, studies, or analyzes the information or biospecimens; or
Obtains, uses, studies, analyzes, or generates identifiable private information or identifiable biospecimens."

Research means “a systematic investigation, including research development, testing and evaluation, designed to develop or contribute to generalizable knowledge.” Human subjects research is at the intersection of these two federal definitions and must obtain Institutional Review Board approval before starting, regardless of the type of design involved. The topic of a human research study varies and can include building a theory or hypothesis, determining patient satisfaction, or testing a medication, tool, device, process, or health intervention, to name a few.

Research studies are classified into a qualitative study, a quantitative study, or a combination of both, called a mixed-methods study. [2] [3] Qualitative studies gather non-numerical data, whereas quantitative research involves collecting numerical data. Other classifications of research studies exist depending on the purpose and utility of the study, [4] examples include health systems research and operational research. [5] This review will be limited to the most common quantitative and qualitative research designs.

Quantitative Research

A research study can be done to describe variables and/or to determine the association of test and outcome variables regarding the research topic. [1] Quantitative research studies also subdivide into either interventional studies or non-interventional (observational) studies. For interventional research studies, the researcher performs some intervention or manipulation of one or more groups in the research study and compares the outcomes to the other groups to help analyze the variables of interest. It may or may not be randomized, although a randomized controlled trial is considered a gold standard, as randomization of patients into the treatment groups reduce bias. Interventional studies apply to medical drugs, biologics, and devices.

For observational or non-interventional research studies, the investigator gathers data for identified variables of interest without any intervention or outside influence by the investigator on the groups under study. Cohort, cross-sectional, and case-control are the common types. [2]

A cohort study involves longitudinally following a group or groups of population with certain known exposures to determine who develops certain diseases or illnesses. This type of study could establish causal relationships between exposure and outcomes such as illness. [2] A cross-sectional study deals with a population at a given point in time as opposed to longitudinally and could provide information such as prevalence. Case-control studies compare populations with and without the exposure to determine if an illness will develop and at what rate in either group. A classic example is comparing smokers and non-smokers to determine which group develops lung cancer.

Qualitative Research

Qualitative research aims to answer the more open-ended questions that arise during the research process. Rather than trying to answer quantitative ‘how much’ or ‘how many’-type questions, qualitative research seeks to answer ‘how’ and ‘why’ questions. [3] Qualitative research often aims to understand and explain why or how a phenomenon is the way it is in order to provide insights and explanations of real-life problems and experiences. [4] Qualitative research can be used alone, in conjunction with quantitative research in mixed methods research, or as a way to explain the findings of a quantitative study because a quantitative study might show that there is a correlation between two things, but a qualitative study could then tell why that correlation exists, and not just that it does indeed exist.

There are many approaches used for qualitative research. Some of the most common are ethnography, grounded theory, phenomenology, and narrative research. [3] Ethnography is an approach that involves the researcher to be immersed in their participant’s environment, and through this immersion, collect insight into the actions, behaviors, and events that could aid them in their research. [4] Grounded theory is an approach where the researcher observes the population of interest in order to develop a theory that explains the topic of interest. [3] Phenomenology as an approach emphasizes the importance of the ‘lived experience’ for explaining phenomena. [4] Grounded theory and phenomenology are similar, but grounded theory focuses on observation as a whole to create a theory, whereas phenomenology focuses on the perspective of participants themselves to explain why or how something happens. Lastly, narrative research showcases one of qualitative research’s strengths, the ability to tell a story. When research includes the perspective of the individuals involved, it can create robust theory-building because it takes into account the real-life implications and impacts of phenomena in a way that quantitative research often lacks. Data for qualitative research is collected in many ways, including interviews, focus groups, case studies, and medical record reviews.

Mixed Methods Research

In some cases, a combination of both qualitative and quantitative methods, or what is called a mixed-methods research is performed. Mixed methods approaches that combine qualitative and quantitative research can allow for hypothesis generation and hypothesis testing to help try to answer questions in a more well-rounded way. This is usually done to get the benefits of both numerical and non-numerical information to answer the research questions on hand. For example, a cross-sectional study found that young teens are vaping at a high rate. For further elucidation of the reasons why these teens vape, a subsequent focus group could be performed.

Issues of Concern

One of the primary concerns in doing research is the identification and formulation of the research problem (i.e., research question). [5] The research problem should be ethical, researchable, significant, and feasible. In medicine, the goal of the research is not only to add relevant findings to the scientific body of knowledge but also to provide a beneficial, useful contribution to stakeholders, particularly the patients.

The second area of concern for research studies is selecting the correct research study to perform. Many times descriptive and qualitative research must first take place to produce a robust, significant, and feasible research hypothesis for later quantitative research methods. [6] Additionally, different research study types have different levels of strength and risk of bias as delineated in the hierarchy of research study designs. [7]

Clinical Significance

The significance of research studies and its findings collectively support both clinical and public health needs. The discovery of new medicines and new treatment modalities for specific diseases is possible using randomized clinical (control) trials, more commonly termed as RCTs. [8] Public health, both as medical and social science, can choose from a wide range of qualitative studies, descriptive, analytic, community-based trials [9] , and operations researches, among others, to explore and describe the characteristics of certain groups of populations and its associations to the disease process or a particular health intervention, yielding findings that will inform policymakers and stakeholders.

In clinical settings, case studies and case series can be used by clinicians, surgeons, and other clinical specialists to scientifically document and describe the occurrence of rare diseases. [10] Researchers can perform studies to determine the association of exposure variables or risk factors in rare diseases or cohort studies to investigate rare exposure variables present in the study population. Meanwhile, studies such as meta-analysis and systematic review are good choices for researchers who want to summarize the results of previous research findings, in quantitative and qualitative means, respectively. [11] [12] Mixed methods are employed to combine and exhaust the utility of the research type or study design combinations (e.g., quantitative and qualitative studies). [13]

Research studies can be both simple and complex; thus, they can be performed in several ways, which must be consistently systematic and scientific. The acquisition of new research findings will eventually find utility in the application of evidence-based medicine (EBM). [14] Research studies must be carried out within the walls of medical ethics, free of bias, and primarily geared towards the welfare of our patients rather than just merely the expedition of science. [15]

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Disclosure: Marlon Bayot declares no relevant financial relationships with ineligible companies.

Disclosure: Grace Brannan declares no relevant financial relationships with ineligible companies.

Disclosure: Janelle Brannan declares no relevant financial relationships with ineligible companies.

Disclosure: Steven Tenny declares no relevant financial relationships with ineligible companies.

This book is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ), which permits others to distribute the work, provided that the article is not altered or used commercially. You are not required to obtain permission to distribute this article, provided that you credit the author and journal.

Cite this Page Bayot ML, Brannan GD, Brannan JM, et al. Human Subjects Research Design. [Updated 2023 Aug 14]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

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What is Customer Research? Definition, Types, Examples and Best Practices

By Nick Jain

Published on: June 26, 2023

Table of Contents

What is Customer Research?

Types of customer research, how to conduct customer research: 10 key steps, examples of customer research questions, top 10 best practices for customer research.

Customer research is defined as the systematic process of gathering and analyzing information about customers, their behaviors, needs, preferences, and experiences. It involves qualitative and quantitative studies to understand the target audience in order to make informed business decisions and develop effective strategies to meet expectations on customer experience and product/ service demands.

Customer research aims to provide insights into various aspects of the customer journey, including their motivations, purchase behaviors, satisfaction levels, and pain points. It helps organizations gain a deep understanding of their customers, enabling them to tailor their products, services, and marketing efforts to better meet customer expectations.

The key components of customer research typically include the following:

Research Objectives: Clearly defining the objectives and goals of the research is crucial. This involves determining what specific information or insights the organization aims to gather from customer research. Research objectives help guide the research process and ensure that the collected data is relevant and aligned with the organization’s needs.
Target Audience Definition: Identifying the target audience or customer segment is essential. This involves determining the specific group of customers or potential customers that the research will focus on. The target audience should be representative of the organization’s customer base or the intended market.
Research Methodology: Choosing the appropriate research methods and techniques is important to gather relevant data. The methodology may include a combination of quantitative and qualitative observation approaches such as surveys, interviews, focus groups , or data analytics. The chosen methods should align with the research objectives and provide the desired depth and breadth of insights.
Data Collection: Conducting data collection activities is a core component of customer research. This involves implementing the selected research methods to collect data from the target audience. It may include distributing surveys, conducting interviews or focus groups , observing customer behaviors, or analyzing existing data sources. Proper data collection techniques ensure the accuracy and reliability of the gathered information.
Data Analysis: Once the data is collected, it needs to be analyzed to extract meaningful insights. Data analysis involves organizing, categorizing, and interpreting the collected data. This may include quantitative research using statistical techniques, such as descriptive statistics or regression analysis, and qualitative research involving the identification of patterns, themes, and trends in the data. The goal is to derive actionable insights that can inform decision-making.
Findings and Insights: Communicating the research findings and insights is a critical component. This involves summarizing and presenting the results in a clear and understandable manner. The findings should address the research objectives and provide valuable insights into customer behaviors, preferences, needs, or pain points. Visualizations, reports, presentations, or dashboards may be used to effectively convey the information.
Recommendations: Based on the research findings, recommendations are made to guide business decisions and actions. Recommendations should be practical, actionable, and aligned with the organization’s goals. They may involve suggestions for product improvements, marketing strategies, customer experience enhancements, market segmentation approaches, or any other relevant areas.
Iteration and Continuous Improvement: Customer research is an iterative process. Organizations should continuously gather customer feedback and update their understanding of customer needs and preferences. The insights gained from research should be regularly incorporated into business strategies and practices. This iterative approach ensures that the organization remains responsive to customer expectations and market changes.

There are various types of customer research that organizations can conduct to gather insights into customer experiences , behavior, and preferences. Some of the common types of customer research include:

Customer Satisfaction Research

Customer satisfaction research focuses on measuring customer satisfaction levels with a product, service, or overall experience. It often involves surveys or feedback forms to gather customer opinions and perceptions. Customer satisfaction research helps organizations identify areas for improvement, gauge customer loyalty, and track changes in customer satisfaction over time.

Customer Needs and Preferences Research

This type of research aims to uncover the needs, preferences, and expectations of customers. It helps organizations understand what customers value, what drives their purchasing decisions, and what features or attributes they desire in a product or service. Customer needs and preferences research can involve surveys, interviews, focus groups , or ethnographic research methods.

Customer Experience (CX) Research

CX research focuses on understanding how users interact with a product, website, or service. It involves observing and analyzing user behaviors, attitudes, and perceptions to identify usability issues, pain points, and opportunities for improvement. The insights gained from CX research help organizations enhance the customer experience and increase satisfaction.

Brand Perception Research

Brand perception research aims to understand how customers perceive a brand and its reputation in the market. It involves gathering customer feedback on brand awareness, brand image, brand associations, and brand loyalty. Brand perception research helps organizations assess the effectiveness of their branding strategies, identify brand strengths and weaknesses, and make informed decisions to enhance brand positioning.

Customer Segmentation Research

Customer segmentation research involves grouping customers into distinct segments based on common characteristics, behaviors, or needs. It helps organizations understand their customer base and tailor their marketing strategies and offerings to specific customer segments. Customer segmentation research can involve data analysis, surveys, or clustering techniques to identify meaningful customer segments.

Competitive Research

Competitive research focuses on analyzing competitors’ strategies, products, and customer experiences . It aims to gain insights into the competitive landscape and identify opportunities for differentiation. Competitive research involves analyzing competitors’ websites, conducting mystery shopping, monitoring social media, and gathering intelligence through industry reports or secondary research.

Customer Journey Mapping

Customer journey mapping involves visualizing and understanding the end-to-end customer experience across various touchpoints and interactions with a company. It helps organizations identify pain points, gaps, and opportunities for improvement at each stage of the customer journey. Customer journey mapping can be done through a combination of data analysis, customer feedback , and qualitative research methods .

These are just a few examples of the types of customer research organizations can conduct. The choice of research type depends on the specific research objectives, the nature of the industry or market, and the information needed to make informed business decisions.

Learn more: What is Customer Feedback?

Conducting customer research involves a systematic approach to gathering insights about customers and their preferences. Here are the key steps to conduct customer research effectively:

1. Define Research Objectives: Clearly define the specific objectives of your customer research. Determine what information or insights you seek to gather and how you plan to use the research findings. This will guide the entire research process and ensure that it remains focused and aligned with your goals.

2. Identify Target Audience: Identify the specific target audience or customer segment you want to study. Consider factors such as demographics, location, behavior, or any other relevant criteria. The target audience should be representative of your customer base or the market you wish to understand.

3. Choose Research Methods: Select the appropriate research methods (such as quantitative , qualitative research ) and techniques that will help you gather the desired information from your target audience. This may include surveys, interviews, focus groups , observational research (such as quantitative , and qualitative observation ), data analytics, or a combination of these methods. Consider the advantages, limitations, and resource requirements of each method.

4. Develop Research Instruments: Design the research instruments, such as survey questionnaires, interview guides, or discussion protocols, based on your research objectives. Ensure that the instruments are clear, concise, and structured to gather the necessary data. Use validated scales or questions when available and pilot test the instruments to identify any issues or areas for improvement.

5. Recruit Participants: Recruit participants who fit your target audience criteria and are willing to participate in the research. Depending on the research methods chosen, recruitment can be done through various channels such as online panels, customer databases, social media, or targeted advertising. Clearly communicate the purpose and benefits of the research to encourage participation.

6. Conduct Data Collection: Implement the chosen research methods to collect data from your participants. Administer surveys, conduct interviews or focus groups , observe customer behaviors, or analyze existing data sources. Ensure that the data collection process follows ethical guidelines, respects privacy, and maintains data confidentiality.

7. Analyze Data: Once the data is collected, analyze it to derive meaningful insights. Use appropriate data analysis techniques based on the nature of your data and research objectives. This may involve quantitative research and analysis using statistical methods, qualitative research and analysis using thematic coding or content analysis, or a combination of both. Ensure that the data analysis is rigorous, systematic, and aligned with your research objectives.

8. Interpret Findings: Interpret the research findings to gain insights into customer behaviors, preferences, needs, or perceptions. Analyze patterns, trends, and relationships in the data and relate them back to your research objectives. Look for key themes, outliers, or significant findings that can inform your decision-making.

9. Communicate Results: Present the research findings in a clear and concise manner. Prepare reports, presentations, or visualizations that effectively communicate the insights to stakeholders. Tailor the communication format to the needs and preferences of your target audience, ensuring that the findings are easily understandable and actionable.

10. Apply Insights: Apply the insights gained from customer research to inform your business decisions and strategies. Use the findings to enhance product development, refine marketing strategies, improve customer experiences , or address specific pain points. Regularly revisit the research findings and incorporate them into your ongoing business practices.

Remember that customer research is an iterative process. As you implement the insights gained, monitor the outcomes and consider conducting follow-up research to assess the impact and gather further insights. Continuous customer research helps organizations stay informed about evolving customer needs and preferences, enabling them to stay competitive and customer-centric.

Learn more: What is Quantitative Market Research?

Here are some examples of customer research questions that businesses might ask:

What factors influenced your decision to purchase our product/service?
How did you first hear about our company?
What specific features or aspects of our product/service do you find most valuable?
What improvements or enhancements would you like to see in our product/service?
How likely are you to recommend our product/service to others? Why?
What obstacles or challenges did you encounter when using our product/service?
How does our product/service compare to competitors in the market?
How satisfied are you with the level of customer support you received?
What are your expectations for pricing and value in relation to our product/service?
How frequently do you use our product/service, and for what purposes?

These questions can help businesses gain insights into customer preferences, satisfaction levels, purchasing behavior, and areas for improvement. It’s important to tailor the questions to the specific industry, product, or service being researched to gather the most relevant information.

When conducting customer research, it’s essential to follow best practices to ensure accurate and valuable insights. Here are some best practices for customer research:

1. Clearly define research objectives

Start by identifying the specific goals and objectives of your customer research. What do you want to learn or achieve through the research? This will guide your research approach and help you focus on the most relevant questions and areas of investigation.

2. Use a mix of qualitative and quantitative methods

Combining qualitative and quantitative research methods can provide a comprehensive understanding of your customers. Qualitative methods , such as interviews or focus groups, offer in-depth insights and allow you to explore customer motivations and experiences. Quantitative methods , like surveys or data analysis, provide statistical data and help you identify patterns and trends.

3. Identify your target audience

Clearly define the characteristics and demographics of your target audience. This will help you select the right participants for your research and ensure that customer feedback represents your customer base accurately.

4. Create unbiased and neutral questions

Formulate questions that are clear, unbiased, and neutral to avoid leading or influencing participants’ responses. Use open-ended questions to encourage participants to provide detailed and honest feedback.

5. Use a variety of data collection methods

Explore various data collection methods to gather customer insights. These can include surveys, interviews, focus groups , social media listening, website analytics, customer feedback forms, or online reviews. Employing multiple methods (such as quantitative research methods , qualitative research methods , etc.) can provide a more comprehensive view of customer opinions and behaviors.

6. Engage with customers at different touchpoints

Interact with customers throughout their journey with your product or service. This can include pre-purchase, purchase, and post-purchase stages. Collect feedback at different touchpoints to understand the entire customer experience and identify areas for improvement.

7. Maintain confidentiality and anonymity

Assure participants that their responses will be kept confidential and anonymous. This encourages honest and unbiased feedback. Respect privacy regulations and data protection guidelines when collecting and storing customer data.

8. Analyze and interpret data systematically

Once you have collected the data, analyze it systematically. Look for patterns, trends, and common themes. Identify key insights and use them to inform your decision-making process. Consider using data visualization techniques to present findings in a clear and concise manner.

9. Continuously iterate and improve

Customer research should be an ongoing process. Regularly revisit your research objectives and update your research methods to reflect changing customer needs and preferences. Continuously gather customer feedback and make improvements based on customer insights.

10. Communicate findings and take action

Share the results of your customer research with relevant stakeholders within your organization. Communicate the key findings, insights, and recommendations. Use the research findings to inform strategic decisions, product development, marketing strategies, and customer support initiatives.

By following these best practices, you can conduct effective customer research that provides valuable insights and helps you better understand and serve your customers.

Learn more: What is Qualitative Research?

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