hypothesis research mcq

MCQs on Hypothesis Testing

This section of Data Science questions and answers include MCQs on Hypothesis Testing. Hypothesis testing is a fundamental statistical concept used to make inferences about a population based on a sample of data. The Hypothesis Testing MCQs address various aspects of hypothesis testing, including definitions, types of errors, significance levels, p-values, effect size, critical regions, and specific tests like t-tests and ANOVA.

1. What is the null hypothesis in a statistical hypothesis test?

a) The hypothesis that there is a significant difference

b) The hypothesis that there is no significant difference

c) The hypothesis that only one variable is involved

d) The hypothesis that the data is perfectly normal

Answer: b) The hypothesis that there is no significant difference

Answer Explanation: The null hypothesis assumes no effect or no difference until evidence suggests otherwise.

2. In hypothesis testing, what is the p-value?

a) The probability of making a Type I error

b) The probability of making a Type II error

c) The probability of observing the data if the null hypothesis is true

d) The probability of rejecting the null hypothesis when it is true

Answer: c) The probability of observing the data if the null hypothesis is true

Answer Explanation: A lower p-value suggests stronger evidence against the null hypothesis.

3. What is a Type I error in the context of hypothesis testing?

a) Incorrectly rejecting a true null hypothesis

b) Incorrectly accepting a false null hypothesis

c) Correctly rejecting a true null hypothesis

d) Correctly accepting a false null hypothesis

Answer: a) Incorrectly rejecting a true null hypothesis

Answer Explanation: Type I error occurs when we falsely conclude that there is an effect when there isn’t.

4. What does the term ‘statistical power’ refer to?

c) The probability of correctly rejecting a false null hypothesis

d) The probability of correctly accepting a true null hypothesis

Answer: c) The probability of correctly rejecting a false null hypothesis

Answer Explanation: Statistical power is the ability to detect a true effect when it exists.

5. Which statistical test is appropriate for comparing means of two independent groups?

b) Chi-square test

d) Pearson correlation

Answer: a) t-test

Answer Explanation: The t-test is used for comparing means of two groups.

6. What is the purpose of the p-value in hypothesis testing?

a) To determine the effect size

b) To quantify the strength of evidence against the null hypothesis

c) To establish causation

d) To calculate the confidence interval

Answer: b) To quantify the strength of evidence against the null hypothesis

Answer Explanation: A lower p-value indicates stronger evidence against the null hypothesis.

7. In a two-tailed hypothesis test, when do you reject the null hypothesis?

a) If the test statistic is too small

b) If the test statistic is too large

c) If the p-value is too small or too large

d) If the p-value is exactly 0.05

Answer: c) If the p-value is too small or too large

Answer Explanation: In a two-tailed test, extreme values in either direction lead to rejection.

8. What is the critical region in hypothesis testing?

a) The range of values where the null hypothesis is likely true

b) The range of values where the null hypothesis is likely false

c) The range of values that leads to rejection of the null hypothesis

d) The range of values that leads to acceptance of the null hypothesis

Answer: c) The range of values that leads to rejection of the null hypothesis

Answer Explanation: The critical region is determined based on the chosen significance level.

9. Which of the following statements about the significance level (α) is correct?

a) It is the probability of rejecting the null hypothesis when it is true

b) It is the probability of accepting the null hypothesis when it is false

c) It is chosen by the researcher and represents the maximum tolerable probability of Type I error

d) It is fixed at 0.05 for all hypothesis tests

Answer: c) It is chosen by the researcher and represents the maximum tolerable probability of Type I error

Answer Explanation: The significance level is a user-defined threshold for the probability of Type I error.

10. What does a confidence interval represent?

c) The range of values that includes the true population parameter with a certain level of confidence

d) The range of values that leads to rejection of the null hypothesis

Answer: c) The range of values that includes the true population parameter with a certain level of confidence

Answer Explanation: A confidence interval provides an estimated range of likely values for a population parameter.

Data Science MCQs on Hypothesis Testing

11. what is the difference between type i and type ii errors in hypothesis testing.

a) Type I error is rejecting a true null hypothesis, while Type II error is accepting a false null hypothesis

b) Type I error is accepting a false null hypothesis, while Type II error is rejecting a true null hypothesis

c) Both Type I and Type II errors involve incorrectly accepting the null hypothesis

d) Both Type I and Type II errors involve incorrectly rejecting the null hypothesis

Answer: a) Type I error is rejecting a true null hypothesis, while Type II error is accepting a false null hypothesis

Answer Explanation: Type I error involves a false positive, while Type II error involves a false negative.

12. In a one-sample t-test, if the p-value is 0.02, what can you conclude?

a) Reject the null hypothesis at a 0.05 significance level

b) Fail to reject the null hypothesis at a 0.05 significance level

c) The null hypothesis is true

d) The test is inconclusive

Answer: a) Reject the null hypothesis at a 0.05 significance level

Answer Explanation: A p-value of 0.02 is less than 0.05, providing evidence to reject the null hypothesis.

13. What is the purpose of the Bonferroni correction in multiple comparisons?

a) To increase the chance of Type I errors

b) To decrease the chance of Type I errors

c) To increase the chance of Type II errors

d) To decrease the chance of Type II errors

Answer: b) To decrease the chance of Type I errors

Answer Explanation: The Bonferroni correction helps control the familywise error rate in multiple comparisons.

14. What is a critical region in a hypothesis test?

c) The range of values that leads to acceptance of the null hypothesis

d) The range of values that leads to neither rejection nor acceptance of the null hypothesis

Answer: b) The range of values where the null hypothesis is likely false

Answer Explanation: The critical region is where the null hypothesis is rejected in favor of the alternative hypothesis.

15. What is the purpose of an effect size measure in hypothesis testing?

a) To determine the statistical power of the test

b) To quantify the strength of a significant result

Answer: b) To quantify the strength of a significant result

Answer Explanation: Effect size helps assess the practical significance of a significant result.

16. Fill in the blank: The ________ is the probability of correctly failing to reject a false null hypothesis.

b) Significance level

c) Type I error rate

d) Type II error rate

Answer: d) Type II error rate

Answer Explanation: Type II error is the probability of accepting a false null hypothesis.

17. In a two-sample t-test, what assumption is made about the variances of the two groups?

a) They must be equal

b) They must be different

c) Variance assumption is not relevant in a t-test

d) The larger variance must be known

Answer: a) They must be equal

Answer Explanation: The assumption of equal variances is crucial for the validity of the t-test.

18. Which statistical test is appropriate for comparing means of more than two independent groups?

a) Paired t-test

b) Wilcoxon signed-rank test

d) Mann-Whitney U test

Answer: c) ANOVA

Answer Explanation: ANOVA is used for comparing means of more than two groups.

19. What is the formula for the standard error of the mean in a one-sample t-test?

a) \( \frac{s}{\sqrt{n}} \)

b) \( \frac{s}{n} \)

c) \( \frac{\sigma}{\sqrt{n}} \)

d) \( \frac{\sigma}{n} \)

Answer: a) \( \frac{s}{\sqrt{n}} \)

Answer Explanation: The standard error of the mean in a t-test is calculated as the sample standard deviation divided by the square root of the sample size.

20. What is the purpose of the Shapiro-Wilk test in hypothesis testing?

a) To test the equality of variances

b) To test the normality of the data

c) To test the independence of observations

d) To test the homogeneity of regression slopes

Answer: b) To test the normality of the data

Answer Explanation: The Shapiro-Wilk test assesses whether a sample comes from a normally distributed population.

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Research Hypothesis Multiple Choice Questions (MCQ) PDF Download

The e-Book Research Hypothesis Multiple Choice Questions (MCQ Quiz) with Answers , Research Hypothesis MCQ PDF download to learn free psychology online courses. Practice Psychological Science Multiple Choice Questions and Answers (MCQs) , Research Hypothesis quiz answers PDF to study psychology degree courses. The Research Hypothesis MCQ App Download: Free learning app for psychological science, scientific method, ensuring that research is ethical test prep for schools that offer certificate programs.

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Research Hypothesis MCQs: Questions and Answers PDF Download

MCQ 1 : A theoretical ideas that form the basis of research hypothesis is:

• Research hypothesis
• Research analysis
• Conceptual variables
• Composed data

MCQ 2 : A attribute, presuming different values among different people in different times or places, known as:

MCQ 3 : The concept which form the basis of a research hypothesis are known as:

• Research Method
• Theory of organisms

MCQ 4 : A concrete statement, prediction of what may happen in a study, termed as:

• Research Tools

MCQ 5 : A variables that consisting of a numbers that represent the conceptual variables are known as:

• Measured variables
• Non vulnerable variables

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MCQ on Hypothesis Testing in Statistics

Statistical hypothesis testing is a method used to assess the validity of claims about data. It involves formulating null and alternative hypotheses, conducting tests, and interpreting results to draw conclusions about population parameters from sample data. This MCQ on Hypothesis Testing will help you to understand the basic concepts and applications of testing of hypothesis.

You may also like : Hypothesis Testing Notes | PPT Hypothesis Testing |

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

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Answer: Hypothesis

Answer: Statistical Hypothesis

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Answer: Level of Significance

Answer: Two tailed

Answer: Test statistic

Answer: Left tailed

Answer: We reject H0 if it is True

Answer: Research Hypothesis

Answer: Reject A True Null Hypothesis

Answer: May Or May Not Be Rejected At The 0.01 Level

Answer: A Type Ii Error Is Committed

Answer: there is not enough statistical evidence to infer that the alternative hypothesis is true

Answer: determine whether a statistical result is significant

Answer: 0.005

Answer: Be greater than 5

Answer: That the underlying population follows an approximately Normal distribution

Answer: the probability of observing the data or more extreme values if the null hypothesis is true

Answer: If the p-value is greater than the significance level, we fail to reject Ho

Answer: 0.025

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• Physics Concept Questions And Answers

Hypothesis Questions

In physics, a hypothesis is a probable explanation for a physical phenomenon. Researchers usually base scientific hypotheses on earlier experiments or observations that cannot evidently be described with the existing scientific theories. At times the words “theory” and hypothesis are used interchangeably. However, a scientific theory is not the same as a scientific hypothesis.

Important Hypothesis Questions with Answers

1) What is a hypothesis?

In science, a hypothesis is a structured assumption that is constructed based on some theoretical or experimental evidence. This is the first step during any research that transforms the investigation queries into predictions. It comprises components like population, variables and the relationship among the variables. Generally, a research hypothesis is a type of hypothesis that is employed to test the connection between multiple variables. For concrete evaluation, the developer of a hypothesis must be able to put forward specifics in functional terms. A hypothesis demands more work by the investigator for both confirming or disproving it. In this process, a confirmed hypothesis could become part of a probable theory or develop into a theory itself. Typically, a scientific hypothesis has the architecture of a mathematical model.

2) Give the fundamental types of hypotheses.

There are mainly six types of hypotheses:

• Simple hypothesis
• Complex hypothesis
• Directional hypothesis
• Non-directional hypothesis
• Null hypothesis
• Associative and causal hypothesis

3) What is meant by a directional hypothesis?

A directional hypothesis is a construct assumption derived by a researcher regarding a negative or positive change, difference, or relationship between two variables among a population. Typically, this prediction is based on previous research, extensive experience or accepted theory. The connection between the variables can also forecast its characteristics. For example, a middle-aged man exercising daily over time has a much lower chance of cardiac arrest than a man who does not follow any exercise routine.

4) What is meant by a non-directional hypothesis?

It is developed when there is no existing theory involved. In most cases, it is a statement that a connection lies between two variables without assuming the exact characteristics (direction) of the inherent connection.

5) What is a theory?

A theory is a scientific method that tries to explain the natural phenomena of the Universe by applying a consistent, systematic, logical way of investigation, data extraction, data scrutiny, experimenting, and refinement to reach a well-tested, thorough explanation that is concretely supported by proofs and evidence.

6) What are the main steps to developing a scientific theory?

Below is a generalised sequence of steps taken to develop a scientific theory:

• Choose and define the natural phenomenon that you need to figure out and describe. Gather data about this phenomenon by examining the source of the phenomena and analysing observations. We can also replicate this phenomenon by an experiment or simulation under a controlled environment (typically inside a laboratory) that removes interference from outside variables.
• After extracting sufficient data, analyse for repeating patterns in the data. Try to describe these recurring patterns by constructing a provisional explanation (hypothesis).
• Test the hypothesis by deriving more information to examine if the hypothesis stays true to exhibit the probable pattern. If the available data does not support the hypothesis, it must be altered or removed for a better one. During the collection of data, we must not ignore information that conflicts with the hypothesis in favour of only supportive information (known as “cherry-picking”). This is frequently misused by pseudo-scientists trying to scam people who are not familiar with scientific methodologies.
• If a concrete hypothesis stands true after all the scrutiny and is the most sound explanation for the phenomenon, then it is considered a valid theory. An established theory may undergo modifications and rejection if there exist enough pieces of evidence that contradict it. Thus, a theory is not a perpetual or absolute truth.

6) What are the main outcomes of a valid hypothesis?

Any valid hypothesis will allow us to make predictions by simple or deductive reasoning. In some scenarios, it could predict the result of a test in a laboratory or the probable observation of a natural process in the Universe. The prediction may give rise to statistics that further point to other extended probabilities or patterns. The scientific method comprises experimentation to validate the hypothesis to sufficiently explain the reasons under thorough investigation.

7) What are the main criteria for formulating a legitimate hypothesis?

During the development of a hypothesis, the researcher must not currently have an absolute prejudice over the probable result of the test or experiment. It should stay reasonably under the scope of the investigation. Then only the experiment or examination increases the probability of deriving a valid, true side of the hypothesis. If the investigator already knows the result, it is only considered a “consequence” (the investigator should have already taken this during the construction of the hypothesis). If the researcher cannot examine the predictions by experience or observation, the hypothesis must be tested by other qualified investigators providing observations.

Investigators examining alternative hypotheses may consider the following:

• Testability
• Parsimony – discouraging the postulation of unrestricted numbers of entities.
• Scope – the apparent application of the hypothesis to many scenarios of the phenomena.
• Fruitfulness – the potential that a hypothesis may help further explain phenomena in the future
• Conservatism – the compatibility with existing recognised knowledge systems.

8) What is a working hypothesis?

A working hypothesis is a type of hypothesis that is scientifically accepted as a foundation for further study in the hope that a plausible theory will be derived, even if the hypothesis eventually fails. Just like most hypotheses, a working hypothesis is created as a statement of assumptions, which can be connected to the exploratory investigation purpose in empirical analysis. They are often employed as an abstract foundation in qualitative research.

Practice Questions

1) What is a postulate? 2) What is the difference between a hypothesis and a theory? 3) What is a pseudo-hypothesis? 4) Define a scientific theory.

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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

Research Methodology Quiz | MCQ (Multiple Choice Questions)

In order to enhance your understanding of research methodology, we have made thought-provoking quiz featuring multiple-choice questions.

This quiz served as a tool to assess your knowledge and comprehension of various research techniques and methodologies. Each question presented unique scenarios, challenging you to analyze and select the most appropriate methodological approach.

The quiz aimed to sharpen your critical thinking skills and reinforce our grasp on essential concepts in the realm of research. By actively participating in this exercise, we deepened your appreciation for the significance of selecting the right research methods to achieve reliable and meaningful results.

Other articles

Please read through some of our other articles with examples and explanations if you’d like to learn more about research methodology.

• PLS-SEM model
• Principal Components Analysis
• Multivariate Analysis
• Friedman Test
• Chi-Square Test (Χ²)
• Effect Size

 Methodology

• Research Methodology Quiz MCQ
• Research Methods
• Quantitative Research
• Qualitative Research
• Case Study Research
• Survey Research
• Conclusive Research
• Descriptive Research
• Cross-Sectional Research
• Theoretical Framework
• Conceptual Framework
• Triangulation
• Grounded Theory
• Quasi-Experimental Design
• Mixed Method
• Correlational Research
• Randomized Controlled Trial
• Stratified Sampling
• Ethnography
• Ghost Authorship
• Secondary Data Collection
• Primary Data Collection
• Ex-Post-Facto
• Table of Contents
•   Dissertation Topic
• Thesis Statement
• Research Proposal
• Research Questions
• Research Problem
• Research Gap
• Types of Research Gaps
• Operationalization of Variables
• Literature Review
• Research Hypothesis
• Questionnaire
• Reliability
• Measurement of Scale
• Sampling Techniques
• Acknowledgements

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Research Methods and Statistics in Psychology

Student resources, multiple choice questions.

Revise your knowledge with these multiple choice quiz questions.

Chapter 2: Research in Psychology: Objectives and Ideals

Chapter 3: Research Methods  

Chapter 4: Experimental Design

Chapter 5: Survey Design

Chapter 6: Descriptive Statistics

Chapter 7: Some Principles of Statistical Inference    

Chapter 8: Examining Differences between Means: The t -test

Chapter 9: Examining Relationships between Variables: Correlation    

Chapter 10: Comparing Two or More Means by Analysing Variances: ANOVA    

Chapter 11: Analysing Other Forms of Data: Chi-square and Distribution-free Tests

Chapter 12: Classical Qualitative Methods

Chapter 13: Contextual Qualitative Methods

Chapter 14: Research Ethics    

Chapter 15: Conclusion: Managing Uncertainty in Psychological Research