data presentation multiple choice questions

• Data Science MCQ Topics
• Linear Algebra
• Data Visualization
• Data Mining
• Machine Learning
• Deep Learning
• Data Analysis
• Business Intelligence
• Pattern Recognition
• Data Science Reference
• Learn Data Science
• Data Science Books
• Data Science Quiz
• Other Reference
• Quantitative Aptitude
• Learn Machine Learning
• Machine Learning Books

Data Visualization MCQs

This section focuses on "Data Visualization" in Data Science. These Data Visualization Multiple Choice Questions (MCQ) should be practiced to improve the Data Science skills required for various interviews (campus interview, walk-in interview, company interview), placements, entrance exams and other competitive examinations.

A. Data Visualization is used to communicate information clearly and efficiently to users by the usage of information graphics such as tables and charts. B. Data Visualization helps users in analyzing a large amount of data in a simpler way. C. Data Visualization makes complex data more accessible, understandable, and usable. D. All of the above

Explanation: Data Visualization is used to communicate information clearly and efficiently to users by the usage of information graphics such as tables and charts. It helps users in analyzing a large amount of data in a simpler way. It makes complex data more accessible, understandable, and usable.

A. It can be accessed quickly by a wider audience. B. It can misrepresent information C. It can be distracting D. None Of the above

Explanation: Pros of data visualization : it can be accessed quickly by a wider audience.

A. graphs B. charts C. maps D. All of the above

Explanation: Data visualization is a graphical representation of quantitative information and data by using visual elements like graphs, charts, and maps.

A. It conveys a lot of information in a small space. B. It makes your report more visually appealing. C. visual data is distorted or excessively used. D. None Of the above

Explanation: It can be distracting : if the visual data is distorted or excessively used.

A. deliver presentation architecture B. data presentation architecture C. dataset presentation architecture D. data process architecture

Explanation: Data visualization is also an element of the broader data presentation architecture (DPA) discipline, which aims to identify, locate, manipulate, format and deliver data in the most efficient way possible.

A. Bullet Graphs B. Bubble Clouds C. Fever Maps D. Heat Maps

Explanation: Fever Maps is not is not used for data visualization instead of that Fever charts is used.

A. Treemaps B. Scatter plots C. Population pyramids D. Area charts

Explanation: Treemaps are best used when multiple categories are present, and the goal is to compare different parts of a whole.

A. Line charts B. Scatter plots C. Population pyramids D. Area charts

Explanation: Line charts. This is one of the most basic and common techniques used. Line charts display how variables can change over time.

A. fisher.test() B. chisq.test() C. Lm.test() D. prop.test()

Explanation: prop.test() is used to inference for 1 proportion using normal approx.

A. anova() B. par() C. plot() D. cum()

Explanation: par() is used to query and edit graphical settings.

A. factor.mosaicplot B. factor.xyplot C. factor.congruence D. factor.cumsum

Explanation: factor.congruence is used to find the factor congruence coefficients.

A. rep() B. data() C. view() D. read()

Explanation: data() load (often into a data.frame) built-in dataset.

A. qqline() B. qline() C. anova() D. lm()

Explanation: qqnorm is another tool for checking normality.

A. lm() B. col.max C. par D. histo

Explanation: lm calls the lower level functions lm.fit.

A. data visualization include the ability to absorb information quickly B. Data visualization is another form of visual art C. Data visualization decrease the insights and take solwer decisions D. None Of the above

Explanation: Data visualization decrease the insights andtake solwer decisions is false statement.

A. par() B. names() C. barchart() D. quantile()

Explanation: names function is used to associate name with the value in the vector.

A. Politics B. Sales and marketing C. Healthcare D. All of the above

Explanation: All option are Common use cases for data visualization.

A. Scientific visualization, sometimes referred to in shorthand as SciVis B. Healthcare professionals frequently use choropleth maps to visualize important health data. C. Candlestick charts are used as trading tools and help finance professionals analyze price movements over time D. All of the above

Explanation: All option are correct.

A. Autocausation B. Autorank C. Autocorrelation D. None of the above

Explanation: If the time series is random, such autocorrelations should be near zero for any and all time-lag separations.

A. par B. lm C. kde D. C

Explanation: kde is used for density plots.

* You must be logged in to add comment.

Have an account?

Suggestions for you See more

Introduction to Data Communications

University  , basic statistics, 10th -  university  , data processing, professional development  .

Presentation, Analysis & Interpretation ...

University - professional development, professional development, science, business.

University -

Professional development, presentation, analysis & interpretation of data.

15 questions

Introducing new   Paper mode

No student devices needed.   Know more

This refers to processes that convert data into information and knowledge

Data Presentation

Data Editing

Data Collection

These are the PROCESSING OPERATIONS

CLASSIFICATION

It is used to filter out irrelevant data from the relevant data and establishing order from chaos and giving shape to a mass of data

Data Reduction

Data Filtering

Data Layering

Data Analysis

It is the process of assigning numerals or other symbols to answers so that responses can be put into a limited number of categories

It is the process of arranging assembled data in a concise/logical manner

Classification

The process of organizing data into logical, sequential and meaningful categories and classifications to make them amenable to study and interpretation

Data Interpretation

This data presentation technique includes books, reports, research papers and articles

Type of graph with rectangular bars that usually compare different categories

Linear Graph

Type of graph that is commonly used to display change over time as a series of data points are connected by straight line segments

Statistical Map

Type of graph that gives a snapshot of how a group is broken down into smaller groups

Type of graph that represents data using images

Type of graph in which the variation in quantity of a factor in a geographical area is indicated

A category of data analysis that is used to find out if there is a relationship between 2 variables

Multivariate

This is the process that helps in reducing a large chunk of data into smaller fragments which make sense

This is a type of data that is expressed in numbers or numerical figures

Qualitative

Quantitative

Categorical

Explore all questions with a free account

Continue with email

Continue with phone

• Create A Quiz
• Relationship
• Personality
• Harry Potter
• Online Exam
• Entertainment
• Training Maker
• Survey Maker
• Brain Games
• ProProfs.com

Data Analysis Quizzes, Questions & Answers

Top trending quizzes.

Popular Topics

Recent quizzes.

MCQ on Graphical Representation of Data

Graphical representation of data uses charts, graphs, and diagrams to visually present information and patterns. It enhances understanding, aids in data analysis, and simplifies complex data, making it accessible to a wider audience. Explore our interactive quiz or MCQ on Graphical Representation of Data to test your comprehension of various graphs, charts, and their applications.

You may also like : Graphical Representation of Data Notes | PPT on Graphical Representation of Data |

You may also like: Biostatistics Notes   |   Biostatistics PPT   |   Biostatistics MCQs   |

<<< Back to Statistics MCQ Page

Related posts:

• MCQ on Measure of Central Tendency
• MCQ on Measure of Dispersion
• MCQ on z Test and its Applications
• MCQ on ANOVA (Analysis of Variance)
• MCQ on Coefficient of Variation

Leave a Comment Cancel reply

Privacy overview.

• Data Structure
• Coding Problems
• C Interview Programs
• C++ Aptitude
• Java Aptitude
• C# Aptitude
• PHP Aptitude
• Linux Aptitude
• DBMS Aptitude
• Networking Aptitude
• AI Aptitude
• MIS Executive
• Web Technologie MCQs
• CS Subjects MCQs
• Databases MCQs
• Programming MCQs
• Testing Software MCQs
• Digital Mktg Subjects MCQs
• Cloud Computing S/W MCQs
• Engineering Subjects MCQs
• Commerce MCQs
• More MCQs...
• Machine Learning/AI
• Operating System
• Computer Network
• Software Engineering
• Discrete Mathematics
• Digital Electronics
• Data Mining
• Embedded Systems
• Cryptography
• CS Fundamental
• More Tutorials...
• Tech Articles
• Code Examples
• Programmer's Calculator
• XML Sitemap Generator
• Tools & Generators

Home » MCQs

Data Analytics Multiple-Choice Questions (MCQs)

The phrase " data analytics " refers to the act of analyzing datasets in order to derive conclusions about the information contained within them. Data analysis techniques allow you to take raw data and derive important insights from it by uncovering patterns.

Many data analytics approaches nowadays rely on specialized systems and software that combine machine learning algorithms, automation, and other features.

Data analytics is a collection of quantitative and qualitative methods for extracting useful information from data. It entails a number of steps, including data extraction and categorization in order to generate numerous patterns, interactions, connections, and other useful insights. Almost every firm has evolved into a data-driven organization today, which means they are implementing a strategy to acquire more data on their customers, markets, and business processes. This information is then classified, saved, and analyzed in order to make sense of it and get useful insights.

Businesses may use data to better understand their consumers, optimize their advertising efforts, tailor their content, and boost their profits. The benefits of data are numerous, but you can't take use of them without the right data analytics tools and methods. While raw data has a lot of promise, data analytics may help you harness the power to build our company. In their research, data scientists and analysts apply data analytics methodologies, and companies use it to guide their judgments. Data analysis may assist businesses in better understanding their clients, evaluating their advertising efforts, personalizing content, developing content strategies, and developing new goods. Finally, firms may employ data analytics to improve their bottom line and raise their performance.

For businesses, the data they employ might be historical data or new information gathered for a specific project. They may also get it directly from their customers and site visitors, or they can buy information from other businesses. Data acquired by a corporation about its own consumers is referred to as first-party data; data obtained from a recognized entity that collected it is referred to as second-party data; and aggregated data purchased from a marketplace is referred to as third-party data. Data regarding an audience's demographics, interests, and actions, among other things, may be used by a firm.

Data Analytics MCQs : This section contains multiple-choice questions and answers on the various topics of Data Analytics.

List of Data Analytics MCQs

1. Data Analytics uses ___ to get insights from data.

• Statistical figures
• Numerical aspects
• Statistical methods
• None of the mentioned above

Answer: C) Statistical methods

Explanation:

To gain insights from data, Data Analytics use statistical approaches. Organizations can use data analytics to uncover trends and develop insights by analyzing all of their data (real-time, historical, unstructured, structured, and qualitative).

Discuss this Question

2. Amongst which of the following is / are the branch of statistics which deals with the development of statistical methods is classified as ___.

• Industry statistics
• Economic statistics
• Applied statistics

Answer: C) Applied statistics

The discipline of statistics that works with the development of statistical procedures is known as applied statistics. Planning for data collecting, maintaining data, analyzing, interpreting, and drawing conclusions from data, and finding issues, solutions, and opportunities utilizing analysis are all part of applied statistics. In data analysis and empirical research, these major fosters critical thinking and problem-solving skills.

3. Linear Regression is the supervised machine learning model in which the model finds the best fit ___ between the independent and dependent variable.

• Linear line
• Nonlinear line
• Curved line
• All of the mentioned above

Answer: A) Linear line

Linear Regression is a supervised Machine Learning model that identifies the best fit linear line between the independent and dependent variables, i.e., the linear connection between the dependent and independent variables.

4. Amongst which of the following is / are the types of Linear Regression,

• Simple Linear Regression
• Multiple Linear Regression
• Both A and B

Answer: C) Both A and B

There are two forms of linear regression: simple and multiple. Simple Linear Regression is used when there is only one independent variable and the model must determine the linear connection between it and the dependent variable. Multiple Linear Regression is employed more than one independent variable in the model to determine the link.

5. Amongst which of the following is / are the true about regression analysis?

• Describes associations within the data
• Modeling relationships within the data
• Answering yes/no questions about the data

Answer: B) Modeling relationships within the data

Regression analysis is used to describe relationships within data, and so it is a collection of statistical methods for estimating relationships between a dependent variable and one or more independent variables. There are various types of regression analysis, including linear, multiple linear, and nonlinear. Simple linear and multiple linear models are the most frequent. Nonlinear regression analysis is typically employed for more difficult data sets with a nonlinear connection between the dependent and independent variables.

6. Linear regression analysis is used to predict the value of a variable based on the value of another variable.

Answer: A) True

Linear regression analysis predicts the value of one variable depending on the value of another. The variable we wish to forecast is referred to as the dependent variable. The variable we are utilizing to predict the value of the other variable is referred to as the independent variable.

7. A Linear Regression model's main aim is to find the best fit linear line and the ___ of intercept and coefficients such that the error is minimized.

• Optimal values
• Linear polynomial

Answer: A) Optimal values

The basic goal of a Linear Regression model is to determine the best fit linear line and the ideal intercept and coefficient values such that the error is minimized. A linear regression model describes the relationship between one or more independent variables, X, and a dependent variable, y. A multiple linear regression model is a type of regression model that has numerous lines of regression. A multiple linear regression model is yi = β 0+ β 1 Xi 1+ β 2 Xi 2+⋯+ βpXip + εi ,  i =1,⋯, n

8. Error is the difference between the actual value and Predicted value and the goal is to reduce this difference.

In statistics, the actual value is the value derived from observation or measurement of the available data. It is also known as the observed value. The expected value is the predicted value of the variable based on the regression analysis. Linear regression is most commonly used to calculate model error using mean-square error (MSE). MSE is derived by measuring the distance between the observed and anticipated y-values at each value of x and then computing the mean of the squared distances.

9. The process of quantifying data is referred to as ___.

• Enumeration

Answer: C) Enumeration

Enumeration is the term for the process of quantifying data. Any quantifiable information that can be used for mathematical calculations or statistical analysis is referred to as quantitative data. This type of information aids in the development of real-world decisions based on mathematical derivations. To answer inquiries like how many, quantitative data is used. How often do you do it? How much is it? This information can be confirmed and validated.

10. Text Analytics, also referred to as Text Mining?

Text analytics uses a combination of machine learning, statistical, and linguistic tools to analyze vast amounts of unstructured material (text that does not have a preset format) in order to draw insights and trends. It enables corporations, governments, researchers, and the media to make critical decisions based on the vast amounts of data available to them.

11. ___ are used when we want to visually examine the relationship between two quantitative variables.

• Scatterplot

Answer: B) Scatterplot

Dots are used to indicate values for two different numeric variables in a scatter plot, also known as a scatter chart or a scatter graph. The values for each data point are indicated by the position of each dot on the horizontal and vertical axes. Scatter plots are used to see how variables relate to one another.

12. A graph that uses vertical bars to represent data is called a ____.

Answer: A) Bar graph

A bar graph is a graph that employs vertical bars to represent data. Bar graphs are visual representations of data (usually grouped) in the shape of vertical or horizontal rectangular bars, with bar length proportional to data measure. Bar charts are another name for them. In statistics, bar graphs are one of the data management methods.

13. Data Analysis is a process of,

• Inspecting data
• Data Cleaning
• Transforming of data

Answer: D) All of the mentioned above

The process of reviewing, cleansing, and manipulating data with the objective of identifying usable information, informing conclusions, and assisting decision-making is known as data analysis. Data analysis is important in today's business environment since it helps businesses make more scientific decisions and run more efficiently.

14. Least Square Method uses ___.

• Linear regression
• Linear sequence

Answer: B) Linear regression

Linear regression employs the Least Square Method. The least-squares approach is a type of mathematical regression analysis that determines the best fit line for a collection of data, displaying the relationship between the points visually. The relationship between a known independent variable and an unknown dependent variable is represented by each piece of data.

15. What is a hypothesis?

• A statement that the researcher wants to test through the data collected in a study
• A research question the results will answer
• A theory that underpins the study
• A statistical method for calculating the extent to which the results could have happened by chance

Answer: A) A statement that the researcher wants to test through the data collected in a studyp

A hypothesis is a proposition that a researcher wishes to evaluate using data from a study. A hypothesis is a conclusion reached after considering evidence. This is the first step in any investigation, where the research questions are translated into a prediction. Variables, population, and the relationship between the variables are all included. A research hypothesis is a hypothesis that is tested to see if two or more variables have a relationship.

16. Linear-regression models are relatively simple and provide an easy-to-interpret mathematical formula that can generate ___.

• Predictions
• Interpretation

Answer: A) Predictions

Linear-regression models are straightforward and provide a basic mathematical method for generating predictions. Linear regression can be used in a variety of corporate and academic study.

17. Amongst which of the following is / are the applications of Linear Regression,

• Social sciences

Linear regression is utilized in a variety of fields, including biology, behavioral science, environmental research, and business. Linear regression models have proven to be a reliable and scientific means of forecasting the future. Because linear regression is a well-known statistical process, its properties are well understood and linear regression models may be trained quickly.

18. With reference to data, dependent and independent variables should be quantitative.

Dependent and independent variables should be quantitative when it comes to data. Both the dependent and independent variables should have a numerical value. Religious, major field of study and residential region categorical factors must be represented as binary variables or other sorts of contrast variables.

19. For each value of the ___, the distribution of the dependent variable must be normal.

• Independent variable
• Depended variable
• Intermediate variable

Answer: A) Independent variable

The dependent variable's distribution must be normal for each value of the independent variable. For all values of the independent variable, the variance of the dependent variable's distribution should be constant. The dependent variable should have a linear relationship with each independent variable, and all observations should be independent.

20. Residual plot helps in analyzing the model using the values of residues.

The residue plot aids in the analysis of the model by displaying the values of the residues. It's shown as a line between the projected values and the residual. Their values are all the same. The point's distance from 0 indicates how inaccurate the prediction was for that number. If the value is positive, the probability of success is minimal. If the value is negative, the probability of success is high. A number of 0 implies that the forecast is perfect. The model can be improved by detecting residual patterns.

21. Amongst which of the following is / are not a major data analysis approach?

• Predictive Intelligence
• Business Intelligence
• Text Analytics

Answer: A) Predictive Intelligence

The practice of collecting data about consumers' and potential consumers' behaviors/actions from a number of sources and perhaps integrating it with profile data about their qualities is known as predictive intelligence.

22. By 2025, the volume of data will increase to,

Answer: C) ZB

It is projected that 2.5 quintillion bytes of data are created every day, with the volume of digital data expected to reach Zeta Byte by 2025.

23. Alternative Hypothesis is also called as?

• Null Hypothesis
• Research Hypothesis
• Simple Hypothesis

Answer: B) Research Hypothesis

The alternative hypothesis is the assertion that is being tested against the null hypothesis. Ha or H1 are common abbreviations for alternative hypotheses. The alternative hypothesis is the hypothesis that is inferred from a null hypothesis that has been rejected. It is best stated as an explanation for why the null hypothesis was rejected. It is also known as the research hypothesis. Unlike the null hypothesis, the researcher is usually most interested in the alternative hypothesis.

24. If the null hypothesis is false then which of the following is accepted?

• Alternative Hypothesis.

The alternative hypothesis is accepted if the null hypothesis is untrue. An alternative theory is a proposition that a researcher is testing in hypothesis testing. From the researcher's perspective, this assertion is correct, and it finally proves to reject the null hypothesis and replace it with a different one. The difference between two or more variables is anticipated in this hypothesis.

25. Amongst which of the following is / are not an example of social media?

Answer: D) None of the mentioned above

Social media is a type of computer-based technology that allows people to share their ideas, thoughts, and information with others via virtual networks and communities. Social media is an internet-based platform that allows people to share content such as personal information, documents, films, and images quickly and electronically.

26. Velocity is the speed at which the data is processed -

The rate at which data is generated, distributed, and gathered is referred to as data velocity. High data velocity is created at such a rapid rate that it necessitates the use of specialized processing techniques. The faster data can be captured and processed, the more valuable the data collected will be and the longer it will hold its worth.

27. ___ refers to the ability to turn your data useful for business.

Answer: A) Value

The ability to turn our data into business value is referred to as value. The usefulness of obtained data for our business is referred to as data value. Data, regardless of its magnitude, is rarely useful on its own; to be useful, it must be transformed into insights or knowledge, which is where data processing comes in.

28. Correlation is the relationship between two variables -

Answer: B) Two

Correlation is the strength of a relationship between two variables, and the Pearson's correlation coefficient measures how strong that relationship is. The correlation of two variables is the statistical link between them. A positive correlation means that both variables move in the same direction, while a negative correlation means that when one variable's value rises, the other variable's value falls.

29. The Mean Squared Error is a measure of the average of the squares of the residuals.

The degree of inaccuracy in statistical models is measured by the mean squared error (MSE). The average squared difference between observed and expected values is calculated. The MSE equals zero when a model has no errors. Its value rises as the model inaccuracy rises. The mean squared deviation is another name for the mean squared deviation (MSD). The average squared residual is represented by the mean squared error in regression.

30. Logistic regression is used to find the probability of event = Success and event = ____.

Answer: A) Failure

The likelihood of event=Success and event=Failure is calculated using logistic regression. When the dependent variable is in nature, we should utilize logistic regression. For classification difficulties, logistic regression is commonly employed. There is no requirement for a linear relationship between the dependent and independent variables in logistic regression. Because it uses a non-linear log transformation on the anticipated odds ratio, it can handle a wide range of relationships.

31. A good data analytics solution includes a viable self-service ___.

• Data mining
• Data wrangling
• Data warehouse

Answer: B) Data wrangling

A smart data analytics solution incorporates self-service data wrangling and data preparation features so that data may be simply and quickly gathered from a range of incomplete, difficult, or messy data sources and cleansed for mashup and analysis.

32. To glean insights from the data, many analysts and data scientists rely on ___.

• Data visualization

Answer: B) Data visualization

Many analysts and data scientists use data visualization, or the graphical depiction of data, to assist individuals visually explores and finds patterns and outliers in the data in order to get insights. Data visualization features are included in a good data analytics system, making data exploration easier and faster.

33. Predictive analytics involves taking historical data -

The approach or practice of utilizing data to generate projections about the possibility of certain future events in your organization is known as predictive analytics, which is a form of advanced analytics. Predictive analytics models unknown future occurrences by combining historical and current data with advanced statistics and machine learning approaches. It is commonly characterized as utilizing data science and machine learning to learn from an organization's previous collective experience in order to make better decisions in the future.

34. With reference to Predictive analytics, it allows organizations to predict customer behavior -

Predictive analytics enables businesses to forecast consumer behavior and business results by combining historical and real-time data. Furthermore, predictive modeling is a subset of this activity that entails constructing and maintaining models, testing and iterating with existing data, and embedding models into applications.

35. Customer analytics refers -

• Customer Relationship Management: churn analysis and prevention
• Marketing: cross-sell, up-sell
• Pricing: leakage monitoring, promotional effects tracking, competitive price responses

Customer analytics includes churn analysis and prevention, marketing: cross-sell and up-sell, and pricing: leakage monitoring, promotional effects tracking, and competitive price reactions.

36. ___ is the cyclical process of collecting and analyzing data during a research study.

• Extremis Analysis
• Constant analysis
• Interim Analysis

Answer: C) Interim Analysis

The cyclical process of gathering and assessing data throughout a research Endeavour is known as interim analysis.

37. An advantage of using computer programs for qualitative data is that they ___.

• Can reduce time required to analyze data
• Help in storing and organizing data
• Make many procedures available that are rarely done by hand due to time constraints

Qualitative data is that they can reduce time required to analyze data, help in storing and organizing data and make many procedures available that are rarely done by hand due to time constraints.

38. Data Modeling is the process of analyzing the data objects -

The practice of evaluating data items and their relationships with other things is known as data modeling. It's utilized to look into the data requirements for various business activities. The data models are constructed in order to store the information in a database.

39. ___ are the basic building blocks of qualitative data.

• Numeric figures

Answer: A) Categories

The fundamental building elements of qualitative data are categories. The descriptive and conceptual results gathered through surveys, interviews, or observation is referred to as qualitative data. We can explore concepts and further explain quantitative outcomes by analyzing qualitative data.

40. Metadata and data modeling tools support the creation and documentation of models -

Models representing the structures, flows, mappings and transformations, connections, and quality of data may be created and documented using metadata and data modeling tools.

41. The Process of describing the data that is huge and complex to store and process is known as ___.

• Analytics mining
• Data cleaning

Answer: C) Big data

Big data is a term used to describe the process of describing data that is large and difficult to store and interpret. Big data analytics is the use of advanced analytic techniques to very large, heterogeneous big data sets, which can contain structured, semi-structured, and unstructured data, as well as data from many sources and sizes ranging from terabytes to zettabytes.

42. In descriptive statistics, data from the entire population or a sample is summarized with ___.

• Numerical descriptor
• Decimal descriptor
• Integer descriptor

Answer: A) Numerical descriptor

Data from the full population or a sample is summarized using numerical descriptors in descriptive statistics.

43. Customer behavior analytics is about understanding how your customers act -

Understanding how your customers behave across each channel and interaction point is the goal of customer behavior analytics. Understanding consumer behavior may aid in customer acquisition, engagement, and retention for your company.

44. Data Analysis is defined by the statistician?

• Hans Peter Luhn
• Gregory Lon

Answer: A) John Tukey

John Tukey, a statistician, defined data analysis. Tukey began his career in statistics, and he was fascinated with data analysis challenges and methodologies. Some people remember him for pioneering exploratory data analysis, but he also made significant contributions to analysis of variance, regression, and a wide range of applications. This study examines some of the most notable contributions in these fields.

45. Amongst which of the following is / are the challenges overcome by the data strategy to make a business in a strong position -

• Data privacy, data integrity, and data quality issues that undercut your ability to analyze data
• Inefficient movement of data between different parts of the business
• Lack of deep understanding of critical parts of the business

Data strategy aids in the development of a strong firm. It also puts a company in a good position to overcome obstacles. Issues with data privacy, integrity, and quality that limit your capacity to evaluate data Lack of understanding of important business components and the processes that keep them run Inefficient data transportation between different portions of the organization, or data duplication by several business units, as well as a lack of clarity about current business needs and goals.

46. Tableau is a ___ tool.

• Visualization
• Data Exploration

Tableau is a visualization software program. Tableau gives data scientists a versatile front-end for data exploration with the analytical depth they need. Data scientists may execute complicated quantitative studies in Tableau and communicate visual findings to encourage improved understanding and collaboration with data by utilizing advanced computations, R and Python integration, quick cohort analysis, and predictive capabilities.

47. Big data analytics refers to collecting, processing, cleaning, and analyzing large datasets -

Big data analytics is the process of gathering, processing, cleaning, and analyzing enormous datasets in order to assist businesses operationalize their data.

48. Amongst which of the following is / are the features of Tableau for data analytics -

• Data Blending
• Real time analysis
• Collaboration of data

Tableau software's finest features are data blending, real-time analysis, and data collaboration. The beautiful thing about Tableau software is that it can be used without any technical or programming knowledge. The tool has piqued the curiosity of people from many walks of life, including business, researchers, and other industries.

49. ___ is a category, also called supervised machine learning methods in which the data is split on two parts.

• Classification

Answer: A) Classification

Classification is a type of supervised machine learning approach in which the data is divided into two parts: a training set and a validation set. A model is trained from the training set by extracting the most discriminative characteristics that are previously connected with known outputs. This model is then tested on a test set, in which we evaluate the learnt model's efficiency by creating appropriate outputs for a particular set of input values.

50. Clustering belongs to ___ data analysis.

• Unsupervised

Answer: B) Unsupervised

Unsupervised data analysis includes clustering. Without any prior knowledge, the data's hidden structure is discovered and emphasized. Popular clustering techniques include K-means, K-nearest neighbors, and hierarchical clustering.

Topic Wise Data Analytics MCQs

• MCQs | Data Analytics – Overview
• MCQs | Data Analytics – Preprocessing and Basics of Big Data
• MCQs | Data Analytics – Sampling
• MCQs | Data Analytics – Measures of Central Tendency in Data Sets

Comments and Discussions!

Load comments ↻

• Marketing MCQs
• Blockchain MCQs
• Artificial Intelligence MCQs
• Data Analytics & Visualization MCQs
• Python MCQs
• C++ Programs
• Python Programs
• Java Programs
• D.S. Programs
• Golang Programs
• C# Programs
• JavaScript Examples
• jQuery Examples
• CSS Examples
• C++ Tutorial
• Python Tutorial
• ML/AI Tutorial
• MIS Tutorial
• Software Engineering Tutorial
• Scala Tutorial
• Privacy policy
• Certificates
• Content Writers of the Month

Copyright © 2024 www.includehelp.com. All rights reserved.

100 multiple-choice questions (MCQs) for biostatistics

1. What is the primary objective of biostatistics? a) To analyze data from clinical trials b) To study biological processes c) To apply statistical methods to biological data d) To develop new medical treatments

2. Which of the following is an example of quantitative data? a) Blood type b) Gender c) Age d) Eye color

3. Which statistical measure is used to describe the spread or dispersion of data points around the mean? a) Median b) Mode c) Variance d) Skewness

4. What is the purpose of a control group in a randomized controlled trial (RCT)? a) To provide a comparison to the experimental group b) To ensure all participants are treated equally c) To maximize the sample size d) To reduce the risk of bias

5. Which type of study design is commonly used to study the causes of diseases? a) Cross-sectional study b) Case-control study c) Cohort study d) Experimental study

6. What is the p-value in hypothesis testing? a) The probability of making a Type I error b) The probability of making a Type II error c) The level of significance d) The probability of obtaining the observed results by chance alone

7. Which statistical test is used to compare means between two groups? a) Chi-square test b) T-test c) ANOVA d) Wilcoxon rank-sum test

8. In a normal distribution, what percentage of data falls within one standard deviation of the mean? a) 34.13% b) 50% c) 68.27% d) 95.45%

9. What does the term “odds ratio” represent in epidemiological studies? a) The difference between two groups’ odds of an event occurring b) The relative risk of an event occurring in one group compared to another c) The absolute risk of an event occurring in one group d) The number needed to treat (NNT) to prevent one event

10. What is the purpose of blinding in a clinical trial? a) To keep the researchers unbiased b) To keep the participants unaware of the treatment they receive c) To prevent confounding variables from affecting the results d) To ensure the sample size is large enough

11. Which of the following measures of central tendency is affected most by extreme outliers? a) Mean b) Median c) Mode d) Standard deviation

12. A researcher is investigating the association between smoking and lung cancer. What type of study design would be most appropriate? a) Randomized controlled trial b) Case-control study c) Cohort study d) Cross-sectional study

13. Which type of bias occurs when participants who do not complete a study differ from those who do? a) Selection bias b) Information bias c) Confounding bias d) Attrition bias

14. Which statistical test is used to analyze the association between two categorical variables? a) T-test b) Chi-square test c) ANOVA d) Pearson correlation coefficient

15. Which of the following is an example of a continuous variable? a) Gender b) Marital status c) Height d) Blood type

16. What does the term “p < 0.05” indicate in hypothesis testing? a) The results are statistically significant b) The results are not statistically significant c) The effect size is large d) The sample size is small

17. In which phase of a clinical trial are potential side effects and safety assessed? a) Phase I b) Phase II c) Phase III d) Phase IV

18. Which measure of dispersion is not affected by extreme values in a dataset? a) Range b) Variance c) Interquartile range (IQR) d) Standard deviation

19. What does the term “confidence interval” represent in statistics? a) The range of values within which the true population parameter is likely to lie b) The margin of error in a statistical estimate c) The probability of rejecting the null hypothesis d) The level of significance

20. Which type of study design is most susceptible to recall bias? a) Randomized controlled trial b) Case-control study c) Cohort study d) Cross-sectional study

21. Which statistical test is used to compare means between multiple groups? a) T-test b) Chi-square test c) ANOVA d) Wilcoxon rank-sum test

22. A researcher is investigating the relationship between age and blood pressure. Which type of correlation is the most appropriate? a) Positive correlation b) Negative correlation c) No correlation d) Partial correlation

23. Which statistical test is used to analyze the association between two continuous variables? a) T-test b) Chi-square test c) Correlation coefficient d) ANOVA

24. What does the term “sensitivity” represent in diagnostic testing? a) The probability of a positive test result in individuals without the disease b) The probability of a positive test result in individuals with the disease c) The ability of the test to correctly identify individuals with the disease d) The ability of the test to correctly identify individuals without the disease

25. In a clinical trial, what is the purpose of randomization? a) To ensure all participants receive the same treatment b) To ensure the study is double-blinded c) To minimize bias and confounding variables d) To increase the likelihood of a statistically significant result

26. What is the difference between a parameter and a statistic in statistics? a) A parameter is a characteristic of a sample, while a statistic is a characteristic of a population. b) A parameter is a characteristic of a population, while a statistic is a characteristic of a sample. c) A parameter is used in descriptive statistics, while a statistic is used in inferential statistics. d) A parameter is used in inferential statistics, while a statistic is used in descriptive statistics.

27. Which type of bias occurs when participants misreport their exposure or outcome status? a) Selection bias b) Information bias c) Confounding bias d) Recall bias

28. What is the purpose of stratified sampling in research studies? a) To increase the sample size b) To reduce the risk of selection bias c) To increase the external validity of the study d) To ensure equal representation of all demographic groups

29. Which of the following is a measure of relative risk in epidemiological studies? a) Odds ratio b) Standard deviation c) Hazard ratio d) Variance

30. In a normal distribution, what percentage of data falls within two standard deviations of the mean? a) 34.13% b) 50% c) 68.27% d) 95.45%

31. Which statistical test is used to compare proportions between two groups? a) T-test b) Chi-square test c) ANOVA d) Wilcoxon rank-sum test

32. What is the purpose of a placebo in a clinical trial? a) To provide a reference point for comparison b) To ensure participants

are blinded to the treatment c) To ensure the study is double-blinded d) To maximize the placebo effect

33. Which type of study design is best suited for establishing cause-and-effect relationships? a) Cross-sectional study b) Case-control study c) Cohort study d) Experimental study

34. Which statistical measure is used to summarize the variability of a sample mean estimate? a) Median b) Mode c) Variance d) Standard error

35. What does the term “type I error” refer to in hypothesis testing? a) Incorrectly rejecting a true null hypothesis b) Incorrectly accepting a false null hypothesis c) Incorrectly rejecting a false null hypothesis d) Incorrectly accepting a true null hypothesis

36. What is the purpose of a two-sample t-test? a) To compare the means of two independent groups b) To compare the means of two paired groups c) To compare the variances of two independent groups d) To compare the proportions of two independent groups

37. In a contingency table, what does the term “marginal totals” represent? a) The total number of observations in each row and column b) The sum of the cell frequencies c) The average value of the cells in each row and column d) The standard deviation of the cell frequencies

38. Which measure of central tendency is most appropriate for ordinal data? a) Mean b) Median c) Mode d) Standard deviation

39. Which of the following statements about the normal distribution is true? a) It is positively skewed. b) The mean, median, and mode are equal. c) The area under the curve is always less than 1. d) It is a discrete probability distribution.

40. What does the term “power” refer to in statistical hypothesis testing? a) The probability of correctly rejecting a false null hypothesis b) The probability of correctly accepting a true null hypothesis c) The level of significance d) The probability of making a Type I error

41. Which statistical test is used to compare means between multiple groups and control for confounding variables? a) T-test b) Chi-square test c) ANOVA d) Regression analysis

42. What is the purpose of the Central Limit Theorem in statistics? a) To determine the sample size needed for a study b) To describe the shape of a normal distribution c) To estimate population parameters from sample statistics d) To calculate the variance of a sample

43. Which type of bias occurs when the study results are influenced by factors other than the exposure or intervention being studied? a) Selection bias b) Information bias c) Confounding bias d) Observer bias

44. What is the purpose of a Kaplan-Meier survival curve? a) To compare the survival rates of different groups over time b) To assess the normality of a distribution c) To estimate the population mean d) To visualize the spread of data points

45. In a chi-square test, what does the chi-square statistic represent? a) The difference between the observed and expected frequencies b) The measure of effect size c) The probability of a Type I error d) The probability of a Type II error

46. Which statistical test is used to analyze the association between a categorical variable and a continuous variable? a) T-test b) Chi-square test c) ANOVA d) Regression analysis

47. In a randomized controlled trial, what is the purpose of intention-to-treat (ITT) analysis? a) To assess the efficacy of the treatment on the per-protocol population b) To minimize the risk of selection bias c) To analyze the data without considering the treatment assignment d) To control for confounding variables

48. Which of the following study designs is most appropriate for investigating rare diseases or outcomes? a) Cross-sectional study b) Case-control study c) Cohort study d) Randomized controlled trial

49. What is the purpose of a p-value in hypothesis testing? a) To determine the effect size of the study b) To assess the statistical power of the study c) To measure the probability of obtaining the observed results by chance alone d) To calculate the margin of error in the study

50. Which statistical measure is used to describe the shape of a distribution? a) Median b) Mode c) Skewness d) Standard deviation

51. What does the term “confidence level” represent in statistics? a) The level of significance used in hypothesis testing b) The probability of making a Type I error c) The probability of making a Type II error d) The level of certainty in the interval estimate

52. Which type of bias occurs when participants are not representative of the target population? a) Selection bias b) Information bias c) Confounding bias d) Sampling bias

53. What is the purpose of a correlation coefficient in statistics? a) To measure the strength of the relationship between two variables b) To determine the direction of causation between two variables c) To calculate the margin of error in a study d) To assess the normality of a distribution

54. Which type of study design is commonly used to study the prevalence of a disease or condition? a) Cross-sectional study b) Case-control study c) Cohort study d) Experimental study

55. Which statistical test is used to compare the means of three or more independent groups? a) T-test b) Chi-square test c) ANOVA d) Wilcoxon rank-sum test

56. What does the term “p-value” stand for in hypothesis testing? a) Probability value b) Population value c) Percentage value d) Power value

57. In a normal distribution, what percentage of data falls within three standard deviations of the mean? a) 34.13% b) 50% c) 68.27% d) 99.73%

58. Which type of bias occurs when the study results are affected by the way data are collected, recorded, or interpreted? a) Selection bias b) Information bias c) Confounding bias d) Observer bias

59. What is the purpose of a placebo in a randomized controlled trial? a) To ensure all participants receive the same treatment b) To provide a reference point for comparison c) To maximize the placebo effect d) To minimize bias and confounding variables

60. Which measure of central tendency is most appropriate for nominal data? a) Mean b) Median c) Mode d) Standard deviation

61. What is the difference between a null hypothesis and an alternative hypothesis in hypothesis testing? a) A null hypothesis states that there is no effect, while an alternative hypothesis states that there is an effect. b) A null hypothesis states that there is an effect, while an alternative hypothesis states that there is no effect. c) A null hypothesis is always rejected, while an alternative hypothesis is always accepted. d) A null hypothesis is always accepted, while an alternative hypothesis is always rejected.

62. Which type of sampling method involves dividing the population into subgroups and then selecting a random sample from each subgroup? a) Simple random sampling b) Stratified sampling c) Convenience sampling d) Cluster sampling

. What does the term “standard deviation” represent in statistics? a) The average value of a dataset b) The spread or dispersion of data points around the mean c) The difference between the highest and lowest values in a dataset d) The proportion of data points that fall within one standard deviation of the mean

64. Which type of study design is best suited for studying the prevalence of a disease at a specific point in time? a) Cross-sectional study b) Case-control study c) Cohort study d) Experimental study

65. Which statistical test is used to compare means between two paired groups? a) T-test b) Chi-square test c) Paired t-test d) Wilcoxon signed-rank test

66. What is the purpose of a sample size calculation in research studies? a) To determine the effect size of the study b) To assess the normality of the distribution c) To estimate the population parameters d) To ensure the study has sufficient statistical power

67. Which type of bias occurs when participants who experience a particular outcome are more or less likely to be included in the study? a) Selection bias b) Information bias c) Confounding bias d) Survivorship bias

68. Which statistical test is used to analyze the association between three or more categorical variables? a) T-test b) Chi-square test c) ANOVA d) Regression analysis

69. In a contingency table, what does the term “expected frequencies” represent? a) The sum of the cell frequencies b) The frequency of a specific event c) The frequency distribution of the variables d) The frequencies that would be expected under the assumption of independence

70. What does the term “alpha level” represent in hypothesis testing? a) The level of significance used to determine statistical significance b) The probability of making a Type I error c) The probability of making a Type II error d) The measure of effect size

71. Which type of bias occurs when the exposure and outcome are measured at the same time, leading to an incorrect association? a) Selection bias b) Information bias c) Confounding bias d) Temporal bias

72. What is the purpose of a hazard ratio in survival analysis? a) To measure the strength of the relationship between two continuous variables b) To compare the means of two independent groups c) To assess the normality of a distribution d) To estimate the relative risk of an event occurring over time

73. Which statistical measure is used to describe the strength and direction of a linear relationship between two continuous variables? a) Median b) Mode c) Correlation coefficient d) Standard deviation

74. In a chi-square test, what does the null hypothesis state? a) There is a significant difference between the observed and expected frequencies. b) There is no significant difference between the observed and expected frequencies. c) The population proportion is equal to the sample proportion. d) The population mean is equal to the sample mean.

75. Which type of study design is most appropriate for investigating the incidence of a disease or outcome over time? a) Cross-sectional study b) Case-control study c) Cohort study d) Experimental study

76. What does the term “effect size” represent in statistics? a) The probability of rejecting the null hypothesis b) The level of significance used in hypothesis testing c) The strength of the relationship between two variables d) The difference between the observed and expected frequencies

77. Which statistical test is used to analyze the association between a categorical variable and a continuous variable while controlling for other variables? a) T-test b) Chi-square test c) ANOVA d) Multiple regression analysis

78. What is the purpose of a scatter plot in data visualization? a) To display the distribution of a single variable b) To compare the means of two independent groups c) To visualize the relationship between two continuous variables d) To summarize categorical data

79. Which type of bias occurs when the study population is not representative of the target population due to non-random selection? a) Selection bias b) Information bias c) Confounding bias d) Sampling bias

80. What is the purpose of a 95% confidence interval? a) To provide a range of values within which the true population parameter is likely to lie b) To determine the level of significance in hypothesis testing c) To calculate the margin of error in a study d) To estimate the standard deviation of a sample

81. Which statistical test is used to analyze the association between two continuous variables while controlling for other variables? a) T-test b) Chi-square test c) ANOVA d) Multiple regression analysis

82. In a randomized controlled trial, what is the purpose of a washout period? a) To ensure all participants receive the same treatment b) To minimize the risk of selection bias c) To eliminate the effects of prior treatments or interventions d) To control for confounding variables

83. What does the term “survival analysis” refer to in biostatistics? a) The analysis of continuous variables over time b) The analysis of survival rates and times in a study population c) The analysis of categorical variables and their associations d) The analysis of the effects of interventions on health outcomes

84. Which type of study design is most appropriate for investigating the natural history of a disease or condition? a) Cross-sectional study b) Case-control study c) Cohort study d) Experimental study

85. What is the purpose of a Z-test in hypothesis testing? a) To compare the means of two independent groups b) To compare the means of two paired groups c) To compare the means of three or more independent groups d) To compare the means of a sample to a known population mean

86. Which statistical test is used to analyze the association between two categorical variables while controlling for other variables? a) T-test b) Chi-square test c) ANOVA d) Multiple logistic regression analysis

87. What is the purpose of a Kaplan-Meier estimator in survival analysis? a) To estimate the population mean b) To calculate the variance of a sample c) To estimate the survival function over time d) To assess the normality of a distribution

88. Which type of bias occurs when participants provide responses that they believe the researcher wants to hear? a) Selection bias b) Information bias c) Confounding bias d) Social desirability bias

89. What is the purpose of a sensitivity analysis in statistical modeling? a) To determine the effect size of the study b) To assess the normality of the distribution c) To estimate the population parameters d) To evaluate the robustness of the results to different assumptions

90. Which statistical measure is used to describe the relationship between two categorical variables in a contingency table? a) Median b) Mode c) Odds ratio d) Standard deviation

91. In a chi-square test, what does the degrees of freedom represent? a) The difference between the observed and expected frequencies b) The number of cells in a contingency table c) The number of categories in a variable d) The number of independent variables in the analysis

92. Which type of

bias occurs when participants are not aware of their exposure or outcome status? a) Selection bias b) Information bias c) Confounding bias d) Recall bias

93. What is the purpose of a confidence interval in hypothesis testing? a) To determine the effect size of the study b) To assess the normality of the distribution c) To estimate the population parameters d) To provide a range of values within which the true population parameter is likely to lie

94. Which statistical test is used to compare means between two independent groups with non-normal distributions or small sample sizes? a) T-test b) Chi-square test c) Mann-Whitney U test d) Wilcoxon signed-rank test

95. What does the term “interquartile range (IQR)” represent in statistics? a) The average value of a dataset b) The spread or dispersion of data points around the mean c) The difference between the highest and lowest values in a dataset d) The range of values that fall within the middle 50% of a dataset

96. Which type of study design is best suited for investigating the incidence of a disease in a specific population over time? a) Cross-sectional study b) Case-control study c) Cohort study d) Randomized controlled trial

97. What is the purpose of a paired t-test? a) To compare the means of two independent groups b) To compare the means of two paired groups c) To compare the variances of two independent groups d) To compare the proportions of two independent groups

98. Which statistical test is used to analyze the association between a continuous variable and a categorical variable with two levels? a) T-test b) Chi-square test c) ANOVA d) Linear regression analysis

99. In a randomized controlled trial, what is the purpose of blinding the participants and researchers? a) To ensure all participants receive the same treatment b) To provide a reference point for comparison c) To minimize bias and confounding variables d) To maximize the placebo effect

100. Which measure of dispersion is resistant to extreme values and outliers in a dataset? a) Range b) Variance c) Interquartile range (IQR) d) Standard deviation

Share this post:

• Click to share on Twitter (Opens in new window)
• Click to share on Facebook (Opens in new window)
• Click to print (Opens in new window)
• Click to email a link to a friend (Opens in new window)
• Click to share on LinkedIn (Opens in new window)
• Click to share on Reddit (Opens in new window)
• Click to share on Tumblr (Opens in new window)
• Click to share on Telegram (Opens in new window)
• Click to share on WhatsApp (Opens in new window)
• Click to share on Mastodon (Opens in new window)

PowerPoint MCQ Questions and Answers

Here are 25 multiple-choice questions (MCQs) about Microsoft PowerPoint, complete with answers and explanations. These questions cover various aspects of PowerPoint’s features and functionalities.

1. What is the default file extension for a PowerPoint presentation?

Explanation:.

The default file extension for a PowerPoint presentation is .pptx in the newer versions of the software.

2. How can you add a new slide to a PowerPoint presentation?

To add a new slide in PowerPoint, go to the Home tab and click on the 'New Slide' button.

3. Which feature in PowerPoint is used to create a visual representation of data?

Charts in PowerPoint are used to create a visual representation of data, making it easier to understand and analyze.

4. What is the purpose of 'Slide Master' in PowerPoint?

The Slide Master is used in PowerPoint to uniformly manage the design and layout of multiple slides in a presentation.

5. How do you apply a transition effect between slides?

Transition effects between slides are applied from the Animations tab under the 'Transition to This Slide' group.

6. What is 'Presenter View' in PowerPoint?

Presenter View in PowerPoint provides a private view for the presenter with notes, a timer, and a preview of the upcoming slide, while the audience sees only the slide.

7. How can you insert a video into a PowerPoint slide?

To insert a video into a slide, go to the Insert tab and choose the Video option, where you can add a video from your PC or online sources.

8. What is the use of 'Notes Page' view in PowerPoint?

The Notes Page view in PowerPoint is used to add speaker notes to each slide, which can be referenced during the presentation but aren't visible to the audience.

9. How can you create a uniform look across your entire presentation in PowerPoint?

Applying a theme in PowerPoint helps create a consistent and uniform look across the entire presentation with coordinated colors, fonts, and effects.

10. Which feature in PowerPoint is used to animate objects on a slide?

The Animation Pane under the Animations tab in PowerPoint is used to add and manage animations for objects on a slide.

11. What is the maximum number of slides that can be added to a PowerPoint presentation?

PowerPoint does not have a specific maximum limit on the number of slides you can add to a presentation, although performance may be impacted with a very high number of slides.

12. How can you hide a slide in PowerPoint?

To hide a slide in PowerPoint, right-click on the slide in the slide thumbnail pane and choose 'Hide Slide'. The slide won't show in Slide Show view but remains in the file.

13. What is the purpose of 'Handout Master' in PowerPoint?

The Handout Master in PowerPoint is used to edit the layout and design of handouts, which can include multiple slides per page for distribution to the audience.

14. How can you align objects in a slide?

To align objects on a slide, use the Align option found in the Arrange group under the Home tab, which offers various alignment options for selected objects.

15. What is the keyboard shortcut to start a slide show from the beginning?

Pressing F5 on the keyboard starts the PowerPoint slide show from the beginning.

16. How do you change the color scheme of a PowerPoint presentation?

To change the color scheme of a presentation, go to the Design tab, click on Variants, and choose from the Colors dropdown.

17. What is 'Rehearse Timings' in PowerPoint?

'Rehearse Timings' in PowerPoint is a feature that helps you practice and time the delivery of your presentation.

18. How can you insert a table into a PowerPoint slide?

To insert a table into a slide, go to the Insert tab and click on the Table button, where you can specify the number of rows and columns.

19. What is the purpose of grouping objects in PowerPoint?

Grouping objects in PowerPoint allows you to combine multiple objects into a single unit, making it easier to move, resize, or format them together.

20. How do you add a sound to a PowerPoint presentation?

To add sound to a PowerPoint presentation, go to the Insert tab and click on the Audio button, where you can choose to insert audio from your PC or online sources.

21. What does 'Slide Sorter' view in PowerPoint allow you to do?

Slide Sorter view in PowerPoint displays thumbnails of all slides, allowing you to easily rearrange the order of the slides in your presentation.

22. How can you convert a PowerPoint presentation into a PDF file?

To convert a PowerPoint presentation into a PDF file, go to the File tab, choose Export, and then select Create PDF/XPS Document.

23. What is the use of 'Slide Show' tab in PowerPoint?

The Slide Show tab in PowerPoint contains options for setting up and starting your slide show, including presenter tools and slide show settings.

24. How do you insert a hyperlink in a PowerPoint slide?

To insert a hyperlink in a PowerPoint slide, right-click on the text or object you want to link and choose 'Hyperlink'. You can link to web pages, email addresses, other slides, and more.

25. What is 'SmartArt' used for in PowerPoint?

SmartArt in PowerPoint is a feature used to create a variety of professional-looking graphics, including diagrams, organizational charts, cycles, and more, to visually represent information.

Related MCQ (Multiple Choice Questions) :

Comptia a+ certification practice test, comptia network+ certification practice test, comptia security+ certification practice test, computer fundamental mcq questions and answers, microsoft word mcq questions and answers, excel mcq questions and answers, tally mcq questions and answers, leave a comment cancel reply.

Your email address will not be published. Required fields are marked *

Save my name, email, and website in this browser for the next time I comment.

Online Computer Science Courses

Chapter 14: Computer Fundamentals Exam Tests

Computer Fundamentals MCQs - Chapter 14

Representation of Data Multiple Choice Questions PDF Download - 1

Free Representation of Data Multiple Choice Questions and Answers (MCQs) , Representation of Data MCQ Quiz PDF, test 1 to study online Computer Fundamentals Course . Practice Two States and Characters MCQs , Representation of Data trivia questions and answers PDF to prepare for job interview. Free learning app: Representation of Data MCQs App Download & e-Book for binary representation of characters, representation of fractions in binary career test for online software development courses.

The Multiple Choice Question (MCQ Quiz): A single unit which is composed of small group of bits is known as ; "Representation of Data" App Download (Free) with answers bug, bit, flag and byte to study online classes courses. Solve two states and characters quiz questions , download Google eBook (Free Sample) to learn free online courses.

Representation of Data Questions & Answers PDF Download : MCQ Quiz 1

MCQ 1 : A single unit which is composed of small group of bits is known as

MCQ 2 : BCD stands for

MCQ 3 : System in which fractions are written by extending binary rotation is called

MCQ 4 : The 'megabytes' of computer storage capacity consists of

MCQ 5 : In BCD code, maximum possible characters set size is

Computer Fundamentals Mock Tests

Representation of data learning app & free study apps.

Download Representation of Data MCQs App to learn Computer Fundamentals MCQ, Representation of Data Learning App, and DBMS MCQ App. Free "Representation of Data" App to download Android & iOS Apps includes complete analytics of history with interactive assessments. Download App Store & Play Store learning Apps & enjoy 100% functionality with subscriptions!

Representation of Data App (Android & iOS)

Computer Fundamentals App (Android & iOS)

DBMS App (Android & iOS)

Digital Image Processing App (Android & iOS)

Computer Fundamentals MCQs eBook Download

Computer Fundamentals MCQ Book PDF

Computer Architecture Mock Tests

Computer fundamentals practice questions, computer architecture mcq with answers, representation of data mcq book questions.

HAPPY NEWS! Download and Enjoy interactive Learning Apps with Complete Analytics of your attempts. Don't Miss TRIAL Premium Insights!

Canadian Citizen Test 2024 4+

Canadian citizenship test prep, designed for ipad.

• 5.0 • 5 Ratings
• Offers In-App Purchases

Screenshots

Description.

Do you want to get Canadian Citizenship? If so, you must pass the Canadian Citizenship Test which is a computer-based test taken by the Canadian authorities. The test contains Multiple Choice questions based on the rights and responsibilities of Canadians and Canada’s: - history - geography - economy - government - laws - symbols Based on the latest Canadian Citizenship Test policy, the applicant must answer 15 out of 20 questions correctly to pass the Canada Citizenship Test. This app contains more than 250 questions which you can practice. All the app's material is based on Discover Canada: The Rights and Responsibilities of Citizenship. Practice with the province-specific questions that you will be asked on the citizenship test. It has been professionally developed keeping in mind the official citizenship study guide: "Discover Canada: The Rights and Responsibilities of Citizenship". This app will help you effectively prepare for the Canadian Citizenship Test and will also help you pass the test in the first Go. Some of the unique features of the app are: - Over 250 questions. - Keeps track of unanswered questions or wrongly answered - Customise the Practice Test based on the number of questions and type of questions - Mock test as per the official "Discover Canada: The Rights and Responsibilities of Citizenship" - Result as per the official "Discover Canada: The Rights and Responsibilities of Citizenship" - Full offline mode. - Study all the questions in one place If you are searching for the study material for the Canadian Citizenship Test, this Canadian Citizenship Test 2024 Application will be very helpful in preparing for the test.

Version 3.1

- bug fixes

Ratings and Reviews

App privacy.

The developer, S Mehta , indicated that the app’s privacy practices may include handling of data as described below. For more information, see the developer’s privacy policy .

Data Used to Track You

The following data may be used to track you across apps and websites owned by other companies:

• Identifiers

Data Not Linked to You

The following data may be collected but it is not linked to your identity:

Privacy practices may vary, for example, based on the features you use or your age. Learn More

Information

• Remove Ads $4.99
• Developer Website
• App Support
• Privacy Policy

More By This Developer

Alabama DMV Permit Practice

Ohio BMV Permit Practice Prep

Indiana BMV Permit Practice

CDL Permit Practice Test Prep

US Citizenship Test : 2024

US DMV Permit Test Prep

You Might Also Like

2023 Canadian Citizenship Test

2024 Discover Canada Test

Canada Citizen Now

Test citizenship Canada 2023

Canadian Citizenship Exam 2023

Canadian Citizenship 2024