what is a research design mcq

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Top 20 Research Design MCQ With Answers

Below given are top 20 important Research Design MCQ with answers. These updated multiple choice questions on research design are helpful for BBA, B Com, MBA, MMS, BMS, B Sc, Engineering, PGDM, M Phil and Ph D students and researchers. These MCQs will help for UGC NET, SET, MPSC, UPSC and other competitive entrance exams.

_______research is based on the measurement of quantity or amount.

A. Qualitative

B. Descriptive

C. Quantitative

D. Numerical

______ describes the present state of affairs as it exists without having any control over variables.

A. Analytical research

B. Descriptive research

C. Applied research

D. Distinctive research

In the _______research, the researcher has to use facts or information already available .

A. Analytical

D. Distinctive

__ ___ research is concerned with qualitative phenomena.

______ is related to some abstract ideas or theory.

A. Contextual research

B. Conceptual research

C. Ideal research

D. Empirical research

______ is data-based, coming up with conclusions that are capable of being verified, by observation or by experiment.

The objective of ______ is the development of hypotheses rather than their testing .

A. Laboratory research

B. Diagnostic research

C. Exploratory research

A ________ refers to some difficulty that a researcher experiences in either a theoretical or practical situation

A. research hypothesis

B. research experience

C. research problem

D. research crisis

_______ as a testable statement of a potential relationship between two or more variables.

Research design is a _________for conducting the marketing research project.

A. strategy

B. framework

C. blueprint

D. both B & C

______ is a hypothetical statements denying what are explicitly indicated in working hypotheses.

A. Null hypotheses

B. Working hypotheses

C. Descriptive hypotheses

D. Relational hypotheses

A Blue print of Research work is known as _______

A. sampling design

B. research design

C. research hypotheses

D. research approach

Research design is a blue print, outline and a _________

A. guidance

D. strategy

The choice of research design is influenced by the ________

A. the nature of the research problem

B. the audiences for the study

C. the researchers’ personal experiences

D. all of the above

A Blue print of Research work is called ____

A. Research design

B. Research Problem

C. Research methods

D. Research tools

_______ affect the choice of research methods .

A. Whether the research is ethical or not

B. Time and money available

C. Aims of the researcher

________ is the name of the conceptual framework in which the research is carried out.

A. Research paradigm

B. Synopsis of Research

C. Research design

D. Research hypothesis

The longitudinal research approach mainly deal with _____

A. Horizontal research

B. Vertical Research

C. Short-term research

D. Long-term research

Authenticity of a research finding is its ____

A. Objectivity

B. Tangibility

C. Originality

D. Validity

Research design is a blue print, outline and a ______

A. Strategy

This is all about solved MCQ on Research Design and related concepts.

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Methodology

• What Is a Research Design | Types, Guide & Examples

What Is a Research Design | Types, Guide & Examples

Published on June 7, 2021 by Shona McCombes . Revised on November 20, 2023 by Pritha Bhandari.

A research design is a strategy for answering your   research question  using empirical data. Creating a research design means making decisions about:

• Your overall research objectives and approach
• Whether you’ll rely on primary research or secondary research
• Your sampling methods or criteria for selecting subjects
• Your data collection methods
• The procedures you’ll follow to collect data
• Your data analysis methods

A well-planned research design helps ensure that your methods match your research objectives and that you use the right kind of analysis for your data.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, other interesting articles, frequently asked questions about research design.

• Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities—start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed-methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

• How much time do you have to collect data and write up the research?
• Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
• Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
• Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

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Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types.

• Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships
• Descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analyzing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study—plants, animals, organizations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

• Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalize your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study , your aim is to deeply understand a specific context, not to generalize to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question .

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviors, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews .

Observation methods

Observational studies allow you to collect data unobtrusively, observing characteristics, behaviors or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what kinds of data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected—for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

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As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are high in reliability and validity.

Operationalization

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalization means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in—for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced, while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method , you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

• How many participants do you need for an adequate sample size?
• What inclusion and exclusion criteria will you use to identify eligible participants?
• How will you contact your sample—by mail, online, by phone, or in person?

If you’re using a probability sampling method , it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method , how will you avoid research bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organizing and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymize and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well-organized will save time when it comes to analyzing it. It can also help other researchers validate and add to your findings (high replicability ).

On its own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyze the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarize your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarize your sample data in terms of:

• The distribution of the data (e.g., the frequency of each score on a test)
• The central tendency of the data (e.g., the mean to describe the average score)
• The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

• Make estimates about the population based on your sample data.
• Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analyzing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

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

• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

A research design is a strategy for answering your   research question . It defines your overall approach and determines how you will collect and analyze data.

A well-planned research design helps ensure that your methods match your research aims, that you collect high-quality data, and that you use the right kind of analysis to answer your questions, utilizing credible sources . This allows you to draw valid , trustworthy conclusions.

Quantitative research designs can be divided into two main categories:

• Correlational and descriptive designs are used to investigate characteristics, averages, trends, and associations between variables.
• Experimental and quasi-experimental designs are used to test causal relationships .

Qualitative research designs tend to be more flexible. Common types of qualitative design include case study , ethnography , and grounded theory designs.

The priorities of a research design can vary depending on the field, but you usually have to specify:

• Your research questions and/or hypotheses
• Your overall approach (e.g., qualitative or quantitative )
• The type of design you’re using (e.g., a survey , experiment , or case study )
• Your data collection methods (e.g., questionnaires , observations)
• Your data collection procedures (e.g., operationalization , timing and data management)
• Your data analysis methods (e.g., statistical tests  or thematic analysis )

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

Operationalization 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, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

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

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

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RESEARCH METHODOLOGY MCQs [2023]

This article includes some of the MCQs from Research Methodology.

• Collecting data
• Formulating a research question
• Analyzing data
• Drawing conclusion
• Meta-analysis
• A conclusion drawn from data analysis
• A summary of research findings
• A measurement of data accuracy
• A statement of predicted relationship between variables
• To identify the research gaps
• To summarize research findings
• To collect primary data
• To analyze data
• The variable that is manipulated by the researcher
• The variable that remains constant throughout the research
• The variable that is measured and observed
• The variable that is not relevant to the research question
• To present research findings
• To provide a rationale for the study
• To establish causality
• To guide the data collection process
• A plan for data analysis
• A method for data collection
• A statistical technique
• A framework for conducting research
• To draw conclusion from data
• To develop research hypotheses
• Chi-squared test
• Analysis of variance (ANOVA)
• Regression analysis
• To provide a baseline for comparison
• To receive the experimental treatment
• To control for confounding variables
• To ensure internal validity
• Research article
• Meta analysis
• Interview transcript
• Large sample size
• Standardize data collection methods
• Emphasis on context and social interactions
• Objectives and detached perspective
• Participant observation
• Structured interviews
• Content Analysis
• Focus Groups
• Understanding the meanings and interpretations of individuals
• Hypothesis testing
• Statistical analysis
• Structured questionnaires
• Experiments
• Interviews and Observations
• What is the prevalence of depression in college students?
• How does gender influence job satisfaction ?
• What is the relationship between income and happiness?
• What are the factors that contribute to successful weight loss?
• Experimental research
• Longitudinal research
• Phenomenology
• Correlation research
• Ethnography
• Correlational Study
• Phenomenological study
• To provide a clear research direction
• Clear and Focused
• Relevant and significant
• Testable and measurable
• Broad and ambiguous
• A sample that is selected by chance
• A sample that is selected based on specific criteria
• A sample that is selected from population in a systematic way
• A sample that is selected based on convenience
• A survey of a large population
• An in-depth investigation of a single individual or group
• An experimental design that tests a hypothesis
• An analysis of existing statistical data
• The group of people who participate in the study
• The larger group from which the participants are selected
• The variables being studied
• THe data collected in the study
• Standard Deviation
• Correlation Coefficient
• Chi-square test
• Randomized controlled trial
• Quasi-experimental design
• Cross-sectional study
• Regression Analysis
• Wilcoxon rank-sum test
• Paired-sample test
• To gather primary data
• To establish the sample size
• To test the research hypothesis
• To refine the research methodology
• Convenience Sampling
• Stratified Sampling
• Cluster Sampling
• Simple Random Sampling
• To summarize and describe data
• To explore relationships between variables
• To interpret qualitative data
• To test hypotheses and make inferences about a population
• Primary data
• Secondary data
• Tertiary data
• A summary of book
• A summary of research study
• A summary of the literature on a particular topic
• A summary of a movie
• Identify the research question
• Identify the study population
• Identify the research hypothesis
• Identify the research methodology
• To provide a summary of the main concepts related to the research topic
• To establish the theoretical foundation for the research study
• To outline the research design and methods
• To report the findings of the research study
• Literature review
• Data analysis
• Research question
• Data collection
• Temporal order
• Covariation
• Association
• Control of confounding variables
• The research question
• The research design
• The data collection method
• The data analysis plan
• A plan for collecting data in as research study
• A plan for analyzing data collected in a research study
• A plan for reporting research findings
• A plan for selecting research participants
• Age of participants in a research study
• Gender of participants in a research study
• Scores on a likert scale in a questionnaire
• Responses to open-ended questions in a survey
• The value that appears most frequently in a dataset
• The average of a dataset
• The middle value of a dataset
• The difference between the highest and lowest values in a dataset
• It is exploratory in nature.
• It is aimed at developing new theories
• It is focused on solving practical problems
• It is conducted without a specific application
• Descriptive bias
• Sampling bias
• Causal bias
• Inferential bias
• The tendency of participants to provide socially desirable responses
• The systematic error in measurement instruments
• The distortion of memory in reporting past events
• The influence of the researcher’s expectations on data collection
• Using random sampling techniques
• Double-blind data collection
• Using multiple data collection methods
• Ensuring strict adherence to research protocols
• A measure of central tendency
• A measure of variability
• A systematic error in data collection
• A random error in data collection
• By using a small sample size
• By using biased data collection instruments
• By using non-random sampling techniques
• By using appropriate data collection and analysis methods

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Free download in PDF Research Design Multiple Choice Questions with Answers for competitive exams. These Research Design Objective Questions with Answers are important for competitive exams MBA, UGC NET, GATE, IBPS Specialist Recruitment Test..

View Answer

Answer: All of the above

Answer: A decision to accept or reject the hypothesis

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Answer: It may not provide access to deviant or hidden activities

Answer: True life stories

Answer: One that encourages the interviewee to say more about a topic

Answer: Extant and research-driven

Answer: No, never under any circumstances

Answer: It is difficult to take notes without arousing suspicion

Answer: Introduction; Literature review; Research methods; Results; Discussion; Conclusion

Answer: Research questions

Answer: Sampling people, newspapers, television programmes etc

Answer: It is not feasible to construct a sampling frame of interactions

Answer: The measures devised for concepts are stable on different occasions

Answer: an ambiguous concept whose meaning depends on how it is defined

Answer: Comparative design

Answer: provide academic support, guidance and critical feedback on your work

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Research Methodology

• Introduction to Research Methodology
• Research Approaches
• Concepts of Theory and Empiricism
• Characteristics of scientific method
• Understanding the Language of Research
• 11 Steps in Research Process
• Research Design
• Different Research Designs
• Compare and Contrast the Main Types of Research Designs
• Cross-sectional research design
• Qualitative and Quantitative Research
• Descriptive Research VS Qualitative Research
• Experimental Research VS Quantitative Research
• Sampling Design
• Probability VS Non-Probability Sampling
• 40 MCQ on Research Methodology

MCQ on research Process

• MCQ on Research Design
• 18 MCQ on Quantitative Research
• 30 MCQ on Qualitative Research
• 45 MCQ on Sampling Methods
• 20 MCQ on Principles And Planning For Research

Q1. What is the first step in the research process?

A) Data analysis

B) Literature review

C) Hypothesis testing

D) Research design

Answer: B) Literature review

Q2. What is the purpose of a research hypothesis?

A) To summarize the research findings

B) To explain the research methodology

C) To predict the outcome of the research

D) To describe the research participant

Answer: C) To predict the outcome of the research

Q3. What is the purpose of formulating a research problem in operational terms?

a) To narrow down the scope of the problem

b) To make the problem more complex

c) To make the problem less specific

d) To discriminate relevant data from irrelevant ones

Answer: d) To discriminate relevant data from irrelevant ones

Q4. What is the purpose of replicating a research study?

a) To confirm that the hypothesis is incorrect

b) To prove that the study was flawed

c) To support the contention that the hypothesis cannot be rejected

d) To provide an opportunity to alter the hypothesis

Answer: c) To support the contention that the hypothesis cannot be rejected

Q5. The research process is:

a) a system of interrelated activities

b) a linear process with no interdependencies

c) a static process with fixed stages

d) a process that can be skipped or altered without consequences

Answer: a) a system of interrelated activities

Q6. Which stage of the research process involves formulating a hypothesis?

b) Stage II

c) Stage III

d) Stage IV

Answer: b) Stage III

Q7. What is a dependent variable in a research study?

A) A variable that is manipulated by the researcher

B) A variable that is not affected by other variables

C) A variable that is measured or observed in response to the independent variable

D) A variable that is controlled by the research participants

Answer: C) A variable that is measured or observed in response to the independent variable

Q8. What is the purpose of data analysis in the research process?

A)To collect data from research participants

B) To test the research hypothesis

C) To review the existing literature

D) To design the research study

Answer: B) To test the research hypothesis

Q9. What is a random sample?

A) A sample selected based on a specific criterion

B) A sample selected using a random process

C) A sample selected based on convenience

D) A sample selected based on the researcher’s judgment

Answer: B) A sample selected using a random process