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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.

You’ll also like Business Research Methods MCQ With Answers .

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  • 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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a research design is mcq

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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a research design is mcq

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Research Design: What it is, Elements & Types

Research Design

Can you imagine doing research without a plan? Probably not. When we discuss a strategy to collect, study, and evaluate data, we talk about research design. This design addresses problems and creates a consistent and logical model for data analysis. Let’s learn more about it.

What is Research Design?

Research design is the framework of research methods and techniques chosen by a researcher to conduct a study. The design allows researchers to sharpen the research methods suitable for the subject matter and set up their studies for success.

Creating a research topic explains the type of research (experimental,  survey research ,  correlational , semi-experimental, review) and its sub-type (experimental design, research problem , descriptive case-study). 

There are three main types of designs for research:

  • Data collection
  • Measurement
  • Data Analysis

The research problem an organization faces will determine the design, not vice-versa. The design phase of a study determines which tools to use and how they are used.

The Process of Research Design

The research design process is a systematic and structured approach to conducting research. The process is essential to ensure that the study is valid, reliable, and produces meaningful results.

  • Consider your aims and approaches: Determine the research questions and objectives, and identify the theoretical framework and methodology for the study.
  • Choose a type of Research Design: Select the appropriate research design, such as experimental, correlational, survey, case study, or ethnographic, based on the research questions and objectives.
  • Identify your population and sampling method: Determine the target population and sample size, and choose the sampling method, such as random , stratified random sampling , or convenience sampling.
  • Choose your data collection methods: Decide on the methods, such as surveys, interviews, observations, or experiments, and select the appropriate instruments or tools for collecting data.
  • Plan your data collection procedures: Develop a plan for data collection, including the timeframe, location, and personnel involved, and ensure ethical considerations.
  • Decide on your data analysis strategies: Select the appropriate data analysis techniques, such as statistical analysis , content analysis, or discourse analysis, and plan how to interpret the results.

The process of research design is a critical step in conducting research. By following the steps of research design, researchers can ensure that their study is well-planned, ethical, and rigorous.

Research Design Elements

Impactful research usually creates a minimum bias in data and increases trust in the accuracy of collected data. A design that produces the slightest margin of error in experimental research is generally considered the desired outcome. The essential elements are:

  • Accurate purpose statement
  • Techniques to be implemented for collecting and analyzing research
  • The method applied for analyzing collected details
  • Type of research methodology
  • Probable objections to research
  • Settings for the research study
  • Measurement of analysis

Characteristics of Research Design

A proper design sets your study up for success. Successful research studies provide insights that are accurate and unbiased. You’ll need to create a survey that meets all of the main characteristics of a design. There are four key characteristics:

Characteristics of Research Design

  • Neutrality: When you set up your study, you may have to make assumptions about the data you expect to collect. The results projected in the research should be free from research bias and neutral. Understand opinions about the final evaluated scores and conclusions from multiple individuals and consider those who agree with the results.
  • Reliability: With regularly conducted research, the researcher expects similar results every time. You’ll only be able to reach the desired results if your design is reliable. Your plan should indicate how to form research questions to ensure the standard of results.
  • Validity: There are multiple measuring tools available. However, the only correct measuring tools are those which help a researcher in gauging results according to the objective of the research. The  questionnaire  developed from this design will then be valid.
  • Generalization:  The outcome of your design should apply to a population and not just a restricted sample . A generalized method implies that your survey can be conducted on any part of a population with similar accuracy.

The above factors affect how respondents answer the research questions, so they should balance all the above characteristics in a good design. If you want, you can also learn about Selection Bias through our blog.

Research Design Types

A researcher must clearly understand the various types to select which model to implement for a study. Like the research itself, the design of your analysis can be broadly classified into quantitative and qualitative.

Qualitative research

Qualitative research determines relationships between collected data and observations based on mathematical calculations. Statistical methods can prove or disprove theories related to a naturally existing phenomenon. Researchers rely on qualitative observation research methods that conclude “why” a particular theory exists and “what” respondents have to say about it.

Quantitative research

Quantitative research is for cases where statistical conclusions to collect actionable insights are essential. Numbers provide a better perspective for making critical business decisions. Quantitative research methods are necessary for the growth of any organization. Insights drawn from complex numerical data and analysis prove to be highly effective when making decisions about the business’s future.

Qualitative Research vs Quantitative Research

Here is a chart that highlights the major differences between qualitative and quantitative research:

In summary or analysis , the step of qualitative research is more exploratory and focuses on understanding the subjective experiences of individuals, while quantitative research is more focused on objective data and statistical analysis.

You can further break down the types of research design into five categories:

types of research design

1. Descriptive: In a descriptive composition, a researcher is solely interested in describing the situation or case under their research study. It is a theory-based design method created by gathering, analyzing, and presenting collected data. This allows a researcher to provide insights into the why and how of research. Descriptive design helps others better understand the need for the research. If the problem statement is not clear, you can conduct exploratory research. 

2. Experimental: Experimental research establishes a relationship between the cause and effect of a situation. It is a causal research design where one observes the impact caused by the independent variable on the dependent variable. For example, one monitors the influence of an independent variable such as a price on a dependent variable such as customer satisfaction or brand loyalty. It is an efficient research method as it contributes to solving a problem.

The independent variables are manipulated to monitor the change it has on the dependent variable. Social sciences often use it to observe human behavior by analyzing two groups. Researchers can have participants change their actions and study how the people around them react to understand social psychology better.

3. Correlational research: Correlational research  is a non-experimental research technique. It helps researchers establish a relationship between two closely connected variables. There is no assumption while evaluating a relationship between two other variables, and statistical analysis techniques calculate the relationship between them. This type of research requires two different groups.

A correlation coefficient determines the correlation between two variables whose values range between -1 and +1. If the correlation coefficient is towards +1, it indicates a positive relationship between the variables, and -1 means a negative relationship between the two variables. 

4. Diagnostic research: In diagnostic design, the researcher is looking to evaluate the underlying cause of a specific topic or phenomenon. This method helps one learn more about the factors that create troublesome situations. 

This design has three parts of the research:

  • Inception of the issue
  • Diagnosis of the issue
  • Solution for the issue

5. Explanatory research : Explanatory design uses a researcher’s ideas and thoughts on a subject to further explore their theories. The study explains unexplored aspects of a subject and details the research questions’ what, how, and why.

Benefits of Research Design

There are several benefits of having a well-designed research plan. Including:

  • Clarity of research objectives: Research design provides a clear understanding of the research objectives and the desired outcomes.
  • Increased validity and reliability: To ensure the validity and reliability of results, research design help to minimize the risk of bias and helps to control extraneous variables.
  • Improved data collection: Research design helps to ensure that the proper data is collected and data is collected systematically and consistently.
  • Better data analysis: Research design helps ensure that the collected data can be analyzed effectively, providing meaningful insights and conclusions.
  • Improved communication: A well-designed research helps ensure the results are clean and influential within the research team and external stakeholders.
  • Efficient use of resources: reducing the risk of waste and maximizing the impact of the research, research design helps to ensure that resources are used efficiently.

A well-designed research plan is essential for successful research, providing clear and meaningful insights and ensuring that resources are practical.

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By gkseries see more questions, research design mcqs | research design multiple choice questions with answers.

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  • research design multiple choice questions with answers

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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a research design is mcq

Research Design Selection MCQs

Educational research and methods mcqs topics.

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Our experts have gathered these Research Design Selection MCQs through research, and we hope that you will be able to see how much knowledge base you have for the subject of Research Design Selection by answering these 40 multiple-choice questions. Get started now by scrolling down!

1: A possible threat to validity in which a participant does not show up for a study at a scheduled time or fails to complete the study is known as_____

A.   Dissolution

B.   Attrition

C.   Turnover

D.   Layoff

2: Choose the correct statement about confound.

A.   It is an anticipated variable

B.   It is an unanticipated variable

C.   Variable is not accounted for in a research study

D.   Both b and c

3: Choose the correct statement about control.

A.   When control is low, neither criterion is met

B.   When control is low, only one criterion is met

C.   When control is high, both criteria are met

D.   Both a and c

4: The variable that is believed to change in the presence of the independent variable is known as_____

A.   Independent variable

B.   Dependent variable

C.   Continuous variable

D.   Categorical variable

5: The extent to which results observed in a study will generalize across settings or environments is known as_____

A.   Construct validity

B.   Ecological validity

C.   Internal validity

D.   External validity

6: The methods and procedures used in an experimental research design to specifically control the conditions under which observations are made to isolate cause-and-effect relationships between variables refers to_____

A.   Test

B.   Experiment

C.   Hypothesis

D.   None of these

7: A possible threat to validity in which a participant does not show up for a study at a scheduled time or fails to complete the study is known as experimental mortality.

A.   True

B.   False

8: In experimental research control the three elements of control required are randomization and _____

A.   Manipulation

B.   Comparison

C.   Control

D.   All of these

9: The extent to which observations made in a study generalize beyond the specific manipulations or constraints in the study is known as _____

10: factor is a presumed _____.

A.   Cause

B.   Effect

C.   Both

D.   None

11: _____ occurs when the participants are selected as part of the treatment group and changes their behavior because they believe they are getting special treatment.

A.   Hawthorne effect

B.   History effect

C.   Experimental mortality

D.   Attrition

12: A possible threat to internal validity in which rates of attrition are different between groups in a study is known as_____

A.   Heterogeneous attrition

B.   Homogeneous attrition

C.   History effect

13: A possible threat to internal validity in which rates of attrition are different between groups in a study is known as_____

14: a threat to population validity in which rates of attrition are about the same in each group is known as_____.

D.   Hawthorne effect

15: The variable that is manipulated in an experiment. The levels of the variable remain unchanged between groups in an experiment.This variable is known as_____

16: a possible threat to internal validity in which the measurement of the dependent variable changes due to an error during the course of a research study is known as_____.

D.   Instrumentation

17: The extent to which a research design includes enough control of the conditions and experiences of participants that it can demonstrate a single unambiguous explanation for a manipulation is known as_____

18: _____ is when a participant who is assigned to the control group may try harder because he or she was not selected to receive the special treatment..

B.   John henry effect

C.   Compensatory rivalry effect

19: Levels of a factor means the specific conditions or groups created by _____ that factor.

A.   Manipulating

B.   Deceiving

C.   Destroying

20: A possible threat to internal validity in which a participant’s physiological or psychological state changes over time during a study is known as_____

C.   Maturation

21: The use of methods and procedures to make observations in which the behavior or event is observed “as is” or without an intervention from the researcher is known as_____

A.   Nonexperimental research design

B.   Quasi experimental research design

C.   Descriptive research design

D.   Correlational research design

22: The extent to which the results observed in a study will generalize across different but related dependent variables is known as_____

A.   Outcome validity

B.   Population validity

23: The extent to which results observed in a study will generalize to the population from which a sample was selected is known as_____

24: the use of methods and procedures to make observations in a study that is structured similar to an experiment, but the conditions and experiences of participants lack some control is known as_____, 25: a variable with levels to which participants are not randomly assigned and that differentiates the groups or conditions being compared in a research study is known as_____.

C.   Quasi independent variable

26: A random procedure used to ensure that participants in a study have an equal chance of being assigned to a particular group or condition is known as_____

A.   Systematic sampling

B.   Random assignment

C.   Focus grouping

27: The use of methods for selecting individuals to participate in a study and assigning them to groups such that each individual has an equal chance of being selected to participate and assigned to a group is known as_____

A.   Equalization

B.   Randomization

C.   Regression

28: Regression toward the mean means _____ in a participant’s performance toward a level or score that is closer to or more typical of his or her true potential.

A.   Change

B.   Shift

C.   Keeping up

D.   Both a and b

29: Research design means the specific methods and procedures used to answer a research question.

30: resentful demoralization is when a participant assigned to the control group may instead feel demoralized or resentful because he or she was selected for the treatment group., 31: the extent to which results observed in a study will generalize across time and at different points in time is known as_____.

B.   Temporal validity

32: The improved performance on a test or measure the second time it is taken due to the experience of taking the test is known as_____

D.   Testing effect

33: _____ is the extent to which the treatment can be generalized, whether the treatment can be implemented as it is conceptualized to other individuals.

A.   Treatment validity

34: The use of methods and procedures to make observations in which the behavior or event being observed is observed “as-is” or without any intervention from the researcher, is called ______.

B.   Quasi-experimental research design

C.   Experimental research design

D.   Hypothetical research design

35: Which research design uses methods and procedures to make observations in a study that is structured similarly to an experiment, but the conditions and experiences of participants lack some control because the study lacks random assignment, includes a preexisting factor, or does not include a comparison/control group?

A.   Pseudo-experimental research design

36: Which of the following words tends to be synonymous with internal validity?

A.   Constraint

B.   Reliability

C.   Cause-and-effect

D.   Generalization

37: A researcher uses a procedure to ensure that participants are observed in one of three groups entirely by chance. Which type of randomization did the researcher use in this example?

A.   Random sampling

C.   Random comparison

D.   Random dancing

38: The_____ is generally associated with higher internal validity, whereas the ______ is generally associated with higher external validity.

A.   Field experiment; laboratory experiment

B.   Laboratory experiment; field experiment

C.   Field experiment; field experiment

D.   Laboratory experiment; laboratory experiment

39: During the Halloween season, a researcher records candy intake when it is in close proximity or far proximity from a participant and finds that participants do not eat any candy at all regardless of where the candy is located. Which of the following provides a likely explanation for this outcome?

A.   Participants matured and now realize that candy has too much sugar and so do not eat candy anymore.

B.   It is a history effect in that participants may have been eating candy more often in general and so may be “sick of” eating candy, which is why they are not eating these foods in the study.

C.   It is a testing effect because participants realize that they are being tested on their ability to determine the nutritional content of candy.

D.   It is most likely that all participants do not like to eat candy because most people do not like the taste of foods that are high in sugar.

40: What is a possible threat to validity in which a participant does not show up for a study at a scheduled time or fails to complete the study?

A.   History effect

C.   Instrumentation

D.   Regression toward the mean

41: Population validity, ecological validity, temporal validity, and outcome validity are all subcategories of ______.

A.   Internal validity

B.   External validity

C.   Causation

D.   Research design

42: Suppose a new drug was found in a study to reduce symptoms of depression immediately following treatment, and in a 1-month, 6-month, and 1-year follow-up test. This study would have a high ______.

A.   Population validity

C.   Temporal validity

D.   Outcome validity

43: Suppose a new drug was found in a study to reduce symptoms of depression immediately following treatment, and in a 1-month, 6-month, and 1-year follow-up test. This study would have a high ______.

44: what is the goal of educational research.

A.   To solve all educational problems in one study

B.   To move forward and advance our knowledge of education

C.   To solve educational problems in your local districts

D.   To ignore the limitations of research designs

45: What is the second element of control in an experiment?

A.   Factors

C.   Manipulation

D.   Observation

46: A ______ is an unanticipated variable not accounted for in a research study, which can include individual differences when random assignment is not used.

A.   Confound

C.   Independent variable

D.   Treatment

47: Regression toward the mean usually occurs when participants are selected from the ______ or ______ percentile in a population.

A.   Middle; extreme

B.   Bottom; missed

C.   Bottom; top

D.   Low-performing; average

48: What kind of validity is demonstrated when the results in a study generalize beyond the specific constraints in a study?

A.   High external validity

B.   Low external validity

C.   High internal validity

D.   Low internal validity

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  • MCQs on sampling in research methodology with answers

MCQs on Sampling in Research Methodology : Answers are given along with the multiple-choice questions.

Sampling: In simple terms, a sample is a part of a thing (generally known as population) and it has the ability to display the qualities and features of the thing, of which it is a part. Whereas Sampling is the process of selecting samples from the entire population.

19 MCQs on sampling in research methodology

Answers of the following MCQs are marked as bold.

  • Sample is a representative unit of the population. Is this statement true or false? 

True  

False 

2. In ______________________ every unit falling after a chosen gap of units is included in the sample. 

Interval sampling   

Simple random sampling 

Purposive sampling 

Cluster sampling 

3. Division of the entire population into different groups and then selection of sample on the basis of proportion of each group in the entire population is called as ___________________. 

Stratified sampling 

Sequential sampling 

Quota sampling 

4. For the study of any population, sampling is conducted because it is __________________. 

Expensive 

Difficult 

time-efficient 

Biased 

5. A researcher divides a heterogeneous population into homogeneous groups, and then draws samples from each group. Which sampling technique is the researcher using? 

Stratified sampling  

Non-probability sampling 

6 What is a sample called if it represents one or few characteristics of the population more than the others? 

Good sample 

Bad sample 

Biased sample  

Ineffective sample 

7 What are the various classifications of sampling? 

Random and purposive 

Stratified and cluster 

Probability and non-probability  

Multi-stage and sequential 

8 Simple random sampling cannot be used in ___________________. 

Large population 

Homogeneous population 

Heterogeneous population  

Legal research 

9 In ____________________, all the units of the universe have an equal chance of being included in the sample. 

Probability sampling  

Judgment sampling 

Interval sampling 

10 What is Tippet’s Table used for? 

Convenience sampling 

To reduce sampling errors 

Simple random sampling  

11 Research can never be without any non-sampling errors, but sampling errors can always be avoided. 

Is the above statement true or false? 

12 Why are sampling traits important in sampling? 

They help us in deciding the sample size. 

They help us to differentiate between useless units and useful units. 

They form the basis of the research questions. 

They are the deciding factor in the inclusion of a unit in the sample. 

13 Characteristics to be studied and the size of the population have no effect on selecting a sampling technique. Is this statement true or false? 

False  

14 Sampling can only be effectively conducted in a homogeneous population which is finite and not in an infinite universe with heterogeneous population. 

15 There are least chances of sampling error in a heterogeneous population. Is this statement true or false? 

16 Studying a sample is a cost-effective method of studying a population. Is this statement true or false? 

17 It is not necessary for a sample to show the same characteristics as the population. Is this statement true or false? 

18 Selection of a sampling unit from a population should be dependent upon the inclusion of another sampling unit. Is this statement true or false? 

19 Population is called as ___________ where the members are identical to one another. 

Universe 

Heterogeneous population 

Finite universe 

Important Terms associated with Sampling are as:

  • Sampling Units
  • Sampling Trait
  • Target Population
  • Sample Size
  • Biased Sample
  • Sampling and Non-sampling Error
  • MCQs on Qualitative Research with answers
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Computational Design

MSCD | PhD-CD

The Computational Design (CD) program investigates creative opportunities and critical issues at the nexus of design and computation. Fundamentally interdisciplinary, it mobilizes Carnegie Mellon University’s computational strengths critically towards design, architecture, and other creative disciplines.

Daniel Cardoso Llach

Associate Professor & CD Track Chair

Daniel Cardoso Llach

With a shared emphasis on critical technical practice, faculty and students in the program draw from fields including computer science, robotics, human-machine interaction, machine learning, art, and science and technology studies to illuminate emerging potentials as well as unforeseen consequences of new technologies in design. The program examines topics including robotically-supported construction, machine learning- and AI-based approaches to design generation and analysis, tangible interaction, shape grammars, responsive environments, digital heritage, computational urban studies, as well as historical and ethnographic investigations into design technologies and technologically-mediated design practices. The program’s research and creative works are frequently discussed, published, and exhibited in leading national and international venues. Inherently interdisciplinary, the program invites students to forge unique curricular paths, closely interacting with field-defining researchers, educators, and mentors in the program and across the university. 

The program offers Master of Science (MS) and Doctor of Philosophy (PhD) degrees, and is well suited to highly inquisitive applicants with technical, creative, and/or critical backgrounds who are motivated to challenge disciplinary boundaries; develop a unique research agenda; and explore the intersection computation and design with creativity, technical rigor, and critical depth.

Master of Science in Computational Design

The Masters of Science in Computational Design is a two-year, research-focused program that prepares students for leading industry positions and advanced studies in the broad field of Computational Design. 

Students in the program develop technical and conceptual skills to a) formulate and develop technologies that reimagine material, sociotechnical, and/or environmental relations in design; b) approach digital systems and human-machine encounters as sites for both creative exploration and critical inquiry; and c) produce a thesis that documents a substantial work of research and a novel contribution to knowledge in the field of Computational Design.

Responsive Robotic Assembly with Heterogeneous Raw Wood. Jiaying Wei, MSCD 2023

The program’s curriculum is structured around a lean sequence of research seminars that builds cohesive cohorts, explores the field’s technical, conceptual, and historical underpinnings, and introduces a variety of approaches to research in the field. Selective courses, special topics seminars, and faculty-led independent studies and research groups delve deeper into technical and critical issues, and help instigate the development of unique theses. With guidance from faculty advisors, students define a sequence of courses providing a solid technical understanding of computational concepts and techniques. The precise choice and sequence is based on each student’s prior skill level and their research orientation. In addition, a vast pool of eligible extra departmental courses gives students the opportunity to enrich their methodological and conceptual toolkits further. During the second year, students form advisory committees and develop their theses. Of publishable, or close to publishable, quality, theses in the program rigorously document the definition, prototyping, and critical interrogation of design-technological systems, and/or their histories and the communities they support. 

The program’s typical duration is four semesters. Students must complete a minimum of 147 units of coursework including a 36 unit thesis for graduation. Proficient candidates with prior relevant experience may be considered for advanced standing, subject to approval of the faculty committee upon admission based on a proposed plan of studies. In all cases, full-time registration must be maintained for the first three semesters.

MSCD Curriculum

Doctor of Philosophy in Computational Design

The Doctor of Philosophy in Computational Design prepares students for careers as leading educators, scholars, and researchers in academia and industry. The program offers students the opportunity to conduct research that explores Computational Design questions in greater technical and critical depth, resulting in novel and original contributions to knowledge in the field.

Students work closely with their advisors throughout all stages of the program. Advisors are responsible for supervising and offering guidance, including working with students in the formulation of an individual plan of studies that supports both technical and conceptual elements of the student’s chosen area of concentration. Advisory committees in the doctoral program in CD must be chaired by a CD Core Faculty member, and must include one external member. External advisors might be at a different Carnegie Mellon University department, at a different institution, or in industry. Faculty currently serving as PhD advisors in the program include Profs Joshua Bard, Daragh Byrne, Daniel Cardoso Llach, and Vernelle Noel. Prospective applicants are encouraged to familiarize themselves with the work of the program and with individual advisors’ recent and ongoing research. 

Students’ doctoral path in CD is punctuated by four milestones. The first is the presentation of a game plan that specifies the student’s area of concentration within the program and a scope of work within that area comprising both a plan of studies and research activities, as well as an advisory committee. The second milestone, usually completed after fulfilling course requirements, is a written and oral examination that gives students the opportunity to demonstrate their command over technical and conceptual aspects of their area of concentration, and their ability to formulate an original research project. The third is the public presentation of their dissertation proposal, a document detailing the dissertation’s conceptual, technical, and methodological components, arguing for its relevance to the field of Computational Design, and demonstrating its viability by documenting completed and ongoing research activities. The final milestone is the public defense of their doctoral dissertation. A doctoral dissertation in CD must be a rigorous, significant, and novel contribution to knowledge in the field. It must be grounded on a deep understanding of the state of the art in the field and their specific area of concentration, as well as a critical awareness of the broader contexts of the research.

^ A Data Informed Workflow in Design for Architecture and Urbanism. Javier Argota Sánchez-Vaquerizo, MSCD 2018

PhD-CD Curriculum

About the Program

The highly selective Computational Design graduate program at the School of Architecture at Carnegie Mellon University is a trailblazer in computational design research and pedagogy. With origins in the late 1960s, it is one of the earliest programs of its kind. Its pioneering focus on applications of computational representation and symbolic AI to design has evolved into a broader inquiry into computational modes of design interaction, materiality, and intelligence, and a sensitivity towards the cultural, material, and historical specificity of computational media in design. Today, the Computational Design program adopts a broad view of computation as a vehicle of design inquiry, as a key technical scaffolding for applied and speculative design research, and as a worthy subject of scholarly analysis and debate. 

More than mere instruments, computational methods and ideas — including those linked to recent developments in machine learning/AI, virtual and augmented reality, and robotics — configure new technical infrastructures and imaginaries. Shaping contemporary spaces, artifacts, materials, and labors, these also configure new conceptions of design and creativity. Embracing this complex context, the Computational Design program works to develop new knowledge that harnesses computational ideas and methods towards humane, ecological, and creative environments, and that reimagines the interplay of the technological, the social, and the material in design.

^ Interfacing the Multiplexer Room: Speculative Spatio-Mediated Assemblages for the Digitally Interfered Home. Policarpo Del Campo Baquera, MSCD 2021

MSCD thesis presentations and discussions at CODE Lab (photo credit: Chitika Vasudeva).

Computational Design students occupy the Computational Design Laboratory (CODe Lab) , a beautiful double-height space strategically located in the Margaret Morrison building’s fourth floor, and its two adjacent suites. Aside from workspaces and an area for presentations and collaborative work, the lab houses a fabrication space equipped with a variety of tools to support research including desktop digital and hand fabrication tools, an electronics workbench, as well as dedicated terminals for specialized data and graphics processing and virtual/augmented reality research. 

In addition, CD students have access to many other School of Architecture and Carnegie Mellon University’s world-class laboratories and facilities, including the Design Fabrication Laboratory (dFAB) and Applied Architectural Robotics Laboratory. They often participate in research and learning activities at other labs including the Frank Ratchye STUDIO for Creative Inquiry , the College of Fine Arts’ research hub, and the Manufacturing Futures Institute at Mill 19 , among others.

Extracurricular activities including yearly lecture series and workshops by leading computational design scholars and practitioners further enrich the program, fostering a vibrant atmosphere of research, learning, and creativity.

Program Faculty

Joshua Bard

Joshua Bard

Associate Professor & Associate Head for Design Research

Daragh Byrne

Daragh Byrne

Associate Teaching Professor

Dana Cupkova

Dana Cupkova

Associate Professor & MSSD Track Chair

Jeremy Ficca

Jeremy Ficca

Associate Professor, MAAD Track Chair & dFAB Lab Director

Sinan Goral

Sinan Goral

Adjunct Faculty

Matthew Huber

Matthew Huber

Special Faculty

Omar Khan

Professor & Head

Kristen Kurland

Kristen Kurland

Teaching Professor

Vernelle A. A. Noel

Vernelle A. A. Noel

Lucian and Rita Caste Assistant Professor in Architecture

Paul Pangaro

Paul Pangaro

Visiting Scholar in Computational Design

Admissions Resources

Are you a current student looking for resources? Handbooks, procedures and other information can be found on the Student Resources page .

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Phil Gusmano

  • UB Directory

a research design is mcq

CEO, Design Principal, Founder

Phil Gusmano headshot.

Phil Gusmano is the CEO and Founder of Crafted Concepts Architecture D.P.C. In 2021, Phil co-founded Crafted Concepts Inc. and Crafted Concepts Development Group.

Before founding Crafted Concepts, Phil spent five and a half years with Cannon Design, where he was an Architectural Designer and Planner, Project Architect, and assisted greatly in the BIM leadership, digital design/renderings, and 3D printing. Phil worked on award-winning projects recognized by the AIA including Sheppard Pratt Hospital Baltimore / Washington Campus. He also served as the Lead Architect and Designer for 201 Ellicott in Buffalo, New York. This mixed-use project located in the core of downtown Buffalo has received honors in Brick by Brick awards and published for its innovation and transformation incorporating a mobility hub, affordable and work force housing, and a fresh food market all on one site.

Phil is a Licensed Architect in the State of New York and part of the American Institute of Architects. Phil has a master’s in architecture from the University at Buffalo where he graduated with multiple Design Excellence Awards for his class 3 years in a row. Additionally, he was the recipient of The Arc King Student Award for best thesis and the R. Buckminster Fuller Award for further design excellence. Phil also completed a nine week study abroad program in Tokyo, Japan.

In addition to Phil’s direct studies, he has spent time in construction trades, as well as digital fabrication in collaboration with local companies such as Rigidized Metals Corp. Phil has served in part on the Rigidized Metals Product Development team and actively collaborated with Crafted Concepts on the TXTR Sound Products.

Phil is now a Passive House Consultant as of December 2023. This certification was important in order to further develop Crafted Concepts' designs according to building sciences, product research and development, and innovation in construction methods, techniques and details.

Outside of work, Phil is a husband, a dog father, home improvement specialist, and a Buffalo Bills Tailgate Chef. Phil loves to cook and finds a way to bring is meticulous craftsman attention to detail into everything he does.

Published February 28, 2024

12:15 p.m. Eastern Time (US and Canada)

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  • Outdoor gear

The Best Filtered Water Bottles

Four filtered water bottles along with replacement filters and straws.

Filtered water bottles let you create better-tasting water almost anywhere you go. After we tested five of them, our pick is the Brita Premium Filtering Water Bottle . Its activated carbon filter removes chlorine compounds, which are used as a disinfectant in most public water supplies and are the cause of the off-flavor that many people dislike about tap water.

But we have reservations about filter bottles in general. Most of them make you suck the water through the filter, and that’s not exactly easy—it’s like drinking a thick milkshake through a straw. And most bottle filters remove only chlorine, not other things you may be concerned about, like lead, PFAS (per- and polyfluoroalkyl substances), and microplastics.

If you have access to another source of filtered water, such as a filter pitcher , office water cooler, or under-sink filter , then using that to fill a reusable water bottle is a more convenient and versatile way to bring along fresh-tasting water that’s likely more thoroughly purified too.

a research design is mcq

Brita Premium Filtering Water Bottle

Fresh-tasting water wherever you are.

Certified to remove chlorine from tap water, this model improves the taste, and it comes in a variety of leakproof designs. But, like all filtered bottles, it needs upkeep and is difficult to drink through.

Buying Options

The Brita Insulated Filtering Water Bottle is NSF/ANSI certified (PDF) to reduce the chlorine disinfectants that can give tap water an unpleasant flavor. The bottle itself is well designed for carrying with you to work, school, outdoor events, and errands. It’s sturdy, didn’t leak a drop in our tests, and was easier to drink from than some of the competition, thanks to its comfortable mouthpiece. It comes in many colors, a few sizes, and both insulated stainless steel and BPA-free plastic (which is not insulated) versions. The plastic version is dishwasher safe for cleaning, and the replacement filters, which last about two months, are less than $3 apiece.

The research

Why you should trust us, who this is for, how we picked and tested, our pick: brita premium filtering water bottle, another good filter bottle if pathogens are a concern, the competition.

In testing and writing about water filters for Wirecutter since 2016, I’ve spoken with the two main US filter-certification organizations, NSF and the Water Quality Association, to understand how their testing is conducted. I’ve interviewed engineers and product managers at many water filter manufacturers to interrogate their technologies and claims. And I’ve spent years just living with and using multiple types of water filters, since overall durability, ease and cost of maintenance, and user friendliness are important considerations in something you use multiple times a day.

A Brita Premium Filtering Water Bottle and a LifeStraw Go Series bottle, side by side.

Filtered water bottles create better-tasting water wherever you go. The kind we tested are aimed at commuters, high school and college students, caretakers, and other people who are always on the move. The bottles are sturdy, attractive, and slip easily into a backpack, purse, briefcase, or messenger bag.

The filters usually work by removing the chlorine disinfectants that give lots of tap water an off flavor. But that’s all most of them do. Most do not protect against other contaminants that may be of concern to you, like lead, PFAS, or bacteria.

The filter bottles we tested (with one exception ) are not meant for hikers and wilderness adventurers. That’s because they aren’t designed to be as small and light as possible, to be compatible with a variety of bottles and storage containers, or to remove disease-causing pathogens from untreated water.

That means they’re also not meant for emergency filtration, such as during a boil-water order following a flood or other natural disasters.

Finally, our testing showed that they’re not practical for children. Most filter bottles require you to suck the water through the filter, and that takes considerable force. Youngsters will have a far easier time using regular bottles filled with water from a filter pitcher or other filtered source.

Frankly, so will adults. Bear that in mind when deciding if you need a filter bottle at all.

Seven filtered water bottles that were part of our testing.

We applied the same criteria for filtered water bottles that we do for filter pitchers and dispensers, faucet-mount filters, and under-sink filters: Any claims that bottles remove heavy metals like lead and mercury, industrial compounds like pesticides, and pathogens like bacteria had to be NSF/ANSI certified or tested to NSF/ANSI or similarly stringent standards by accredited independent labs, with the test results publicly shared.

For filter bottles that claim only to make water taste better—which is by far the most common claim—we didn’t require stringent certification, because that’s an extremely simple thing to do. You just run the water through an activated-carbon filter, which are cheap and widely produced.

We did limit our search to filter bottles from well-known brands that have a history in the filtration sector. Numerous filter bottles are now available from small, little-known companies, and though many of them likely perform just fine, we place a lot of emphasis on accountability and an established record in an area as central to well-being as clean drinking water.

We eliminated bottles with pour-through filters, where you fill an upper reservoir and wait for the water to drip through the filter via gravity. They’re slow, and they take several fillings of the upper reservoir to create a full bottle of water—the opposite of on-the-go convenience.

Our testing focused on livability and usability factors. Is a bottle comfortable to hold? To drink from? To refill and to clean? Because filter bottles are generally tall and narrow, their interiors are hard to wash by hand, so we gave points to dishwasher-safe models.

We also came to prefer bottles whose mouthpiece is covered by a cap when not in use. Some have exposed flip-up mouthpieces, and though they’re convenient, they can also pick up dirt while jostling around inside a bag.

We filled our test bottles and kept them upside-down for several hours, shaking them vigorously every 30 minutes or so, to check for seepage. A spill inside your bag is annoying at best, and quite expensive if it ruins some electronics.

We assessed if replacement filters are easily available and affordable. Filters have finite lifespans; you’ll need a new one every few months if you use your filter bottle daily.

A Brita Premium Filtering Water Bottle, our pick for the best filtered water bottle.

The BPA-free plastic Brita Premium Filtering Water Bottle is our pick among the filter bottles we tested. It’s sturdy, comes in a variety of colors and sizes , and is NSF/ANSI certified to reduce chlorine (PDF) , which is the main culprit in bad-tasting tap water. (Note that the plastic versions we recommend are not insulated, although some listings online label them as such. The insulated stainless steel versions keep water cold longer.) Here’s what we liked about the Brita bottle:

A Brita Premium Filtering Water Bottle with its flip-top cap and straw-like filter lying in front of it.

It’s relatively easy to drink from. The effort required to suck water through the straw-like filter is lower than with some competitors—though it’s still like drinking a thick milkshake through a straw—and the soft, rubbery mouthpiece is a comfortable size and shape.

It can make tap water taste better. The bottle uses a simple activated-carbon filter. It efficiently captures the chlorine compounds that are commonly used to disinfect water supplies, which, to many people, make the water taste bad.

Close-up of the flip-top cap and mouthpiece on the Brita Premium Filtering Water Bottle.

The flip-top cap allows for one-handed drinking. The cap protects the mouthpiece and keeps it clean when you’re not using it. You just press a button, and the cap pops open to let you take a drink. We preferred its convenience to bottles with twist-off caps, which require two hands and can be dropped or lost. And we preferred both of these designs to bottles with flip-up spouts, which aren’t protected by a cap and can pick up dirt inside a bag or purse.

We didn’t experience any leaks. To test for leaks, we filled all of our contenders then placed them upside down for several hours, giving them a vigorous shake every half hour. The Brita bottle didn’t leak a drop (and neither did any of the other bottles).

The plastic parts are dishwasher safe. Like any reusable bottle, the Brita bottle should be cleaned regularly. To clean yours in the dishwasher, remove the filter from its housing and then place the housing and all other parts on the top rack. (Brita said the stainless versions should be hand-washed.)

Replacement filters are inexpensive. The replacement filters (model BB06) cost less than $3 apiece. They’re rated to last for 40 gallons or two months.

Flaws but not dealbreakers

This is a flaw of the category, not the Brita bottle specifically, but it bears emphasizing: Filter bottles are harder to drink from and fussier to refill than plain reusable bottles. It takes real effort to suck water through the filter. The straws drip when you pull them out to refill the bottle, and they’re just one more thing you have to clean and maintain.

If you have a convenient source of filtered water available—from an office water cooler, say, or a pitcher or under-sink filter at home—you’ll probably be happier with a versatile reusable bottle such as the ones we recommend .

The carry handle on the Brita bottle is attached to the flip-up cap. That puts the weight of the entire bottle on the small plastic latch that keeps the cap closed. Using the handle to pick up the bottle shouldn’t stress the latch too much, but we would not recommend carrying the bottle by the handle, hanging it from a carabiner while walking around, or pulling the bottle out of an overstuffed bag by yanking on it.

A LifeStraw Go Series filtered water bottle.

If you’d like a filter bottle that both makes treated water taste better (by removing chlorine) and also removes bacteria and protozoa (like Giardia ) that can be present in untreated water, we recommend the BPA-free plastic LifeStraw Go Series bottle . It comes in multiple colors and two sizes (22 and 34 ounces), and an insulated stainless steel version is available in 24 and 34 ounces.

All of LifeStraw’s bottles use a dual filter, with an activated carbon element to reduce chlorine and a hollow fiber membrane filter that physically blocks waterborne bacteria, protozoa, and other particles above 0.2 microns in diameter, including microplastics. (It does not capture viruses, which are smaller still.) You can read LifeStraw’s in-house and independent test results here (PDF) .

The hollow fiber membrane filter takes more strength to suck water through than the Brita Premium Filtering Water Bottle’s plain carbon filter, and because pathogens are not present at dangerous levels in properly treated tap water, the Go bottle is overkill for most everyday use. However, if you travel frequently to places where unsanitary tap water is a concern, the Go bottles are more convenient (and stylish) than camping-oriented filters or chlorine tablets.

A LifeStraw Go Series filtered water bottle on its side with its screw-on cap next to it.

A screw-on cap protects the bottle’s mouthpiece from dirt when it’s not in use, and it prevented any leaks in our testing. However, it requires two hands to use, and while detached, it can be dropped, lost, or separated from its companion in a dish rack or crowded cabinet.

The carry handle is molded right into the lid, and it’s sturdy enough to stand up to moderately rough trail hiking. Commendably, LifeStraw sells replacement carbon filter elements on their own. They need to be switched out far more frequently (every 26 gallons, or about two months) than the hollow fiber filter , which is good for 1,000 gallons.

The Larq Bottle Flip Top effectively reduces lead and some industrial compounds as well as chlorine, which is unusual for a filter bottle. Larq shares the test results (PDF) publicly, as we require. But it has a pop-up mouthpiece that’s always exposed to dirt and other schmutz. And the filter—which is necessarily denser in order to be more capable—takes more strength to suck water through than our top pick from Brita. Replacement filters are also expensive at about $15 to $20 every two months. A regular bottle filled from a filtered water source is a better option if you want extensive purification.

The Phillips GoZero Filtration Bottle is similar to our pick, the Brita Premium Filtering Water Bottle, in form and functionality, but its mouthpiece is shorter and harder to grip between your lips, so it’s more difficult to suck from.

The cleverly designed Grayl 24oz GeoPress Purifier is intended for camping and adventure travel, and we tested it largely to see if it might be a surprise winner for urban and suburban adventures, too. We found that it isn’t: Its plunger action, in which you fill the container and then force the filter through the water, requires a lot of strength and a location where you wouldn’t mind a few splashes. It would be a conversation starter in an office or classroom, but it belongs in the great outdoors.

This article was edited by Harry Sawyers.

Meet your guide

a research design is mcq

Tim Heffernan

Tim Heffernan is a senior staff writer focusing on air and water quality and home energy efficiency. A former writer for The Atlantic, Popular Mechanics, and other national magazines, he joined Wirecutter in 2015. He owns three bikes and zero derailleurs.

Further reading

A few water pitchers and filters standing alongside several glasses of water.

The Best Water Filter Pitcher and Dispenser

by Tim Heffernan

Water filters and pitchers are the simplest, most affordable way to get reliable filtered water at home.

Pur Advanced Faucet Water Filtration System attached to a faucet

The Best Faucet-Mounted Water Filter

Here are our picks for the best water filter to mount on a kitchen faucet.

assorted pet drinking fountains of various sizes and shapes outdoors on a wooden surface

The Best Water Fountain for Cats and Dogs

by Rebekah Valentine

After testing 13 pet water fountains (and having one turned into a chew toy), we think the Catit Flower Fountain is the best for most cats (and some dogs).

Four under-sink water filtration systems sitting on a blue background.

The Best Under-Sink Water Filter

The Aquasana AQ-5200 is the under-sink water filtration system we recommend.

Career or kids: It’s a tough choice for these women

This is part one of a two-part series. Click here to meet the change-makers in a nation of rigid gender norms.

About this story

Design and development by Jake Crump. Animations and graphics by Daron Taylor. Additional research by Min Joo Kim.

Editing by Reem Akkad, Neeti Upadhye, Joseph Moore and Anna Fifield. Copy editing by Vanessa Larson.

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  25. Phil Gusmano

    February 28, 2024 Gusmano shares his professional journey as CEO and Founder of Crafted Concepts Architecture D.P.C. Before founding Crafted Concepts, Gusmano spent five and a half years with Cannon Design, where he was an Architectural Designer and Planner, Project Architect, and assisted greatly in the BIM leadership, digital design/renderings, and 3D printing.

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