Education and Research MCQ Quiz - Objective Question with Answer for Education and Research - Download Free PDF
Last updated on Jul 15, 2025
Latest Education and Research MCQ Objective Questions
Education and Research Question 1:
Which of the following best defines Type II error?
Answer (Detailed Solution Below)
Option 1 : Accepting the null hypothesis when it should be rejected
Education and Research Question 1 Detailed Solution
Correct Answer: Accepting the null hypothesis when it should be rejected
Rationale:
- A Type II error, also known as a "false negative," occurs when the null hypothesis is incorrectly accepted when it should have been rejected. This means that the test fails to detect an effect or difference that actually exists.
- In statistical hypothesis testing, the null hypothesis (H0) represents a default assumption, usually stating that there is no effect or no difference. A Type II error happens when the test lacks enough power or sensitivity to identify a true effect.
- The probability of committing a Type II error is denoted by the symbol β. The complement of β (1 - β) is the test's power, which reflects the likelihood of correctly rejecting the null hypothesis when it is false.
- Type II errors are often a concern in research as they can lead to missed opportunities to discover meaningful results. For instance, in medical research, this might mean failing to identify an effective treatment.
Explanation of Other Options:
Rejecting the null hypothesis when it should be accepted
- Rationale: This describes a Type I error, not a Type II error. A Type I error, also known as a "false positive," occurs when the null hypothesis is rejected even though it is true. It represents finding an effect or difference when none exists. The probability of committing a Type I error is denoted by α, which is typically set at 0.05 (5%) in many studies.
Failing to reject a true null hypothesis
- Rationale: This is not a Type II error. Failing to reject a true null hypothesis is actually a correct decision in hypothesis testing. There is no error in this scenario, as the null hypothesis is indeed true and is appropriately not rejected.
Incorrectly calculating the p-value
- Rationale: This option does not relate to Type II error. Incorrectly calculating the p-value refers to a procedural or computational mistake in analyzing data, which can lead to incorrect conclusions, but it is not directly tied to Type I or Type II errors.
Conclusion:
- Type II errors are critical to understand in hypothesis testing as they reflect the inability to detect a true effect when one exists. Researchers aim to minimize Type II errors by increasing the sample size, ensuring appropriate experimental design, and using tests with high statistical power.
Education and Research Question 2:
Which of the following is the best measure of central tendency in a normally distributed dataset?
Answer (Detailed Solution Below)
Option 3 : Mean
Education and Research Question 2 Detailed Solution
Correct Answer: Mean
Rationale:
- The mean is the most appropriate measure of central tendency for a normally distributed dataset because it takes into account all data points and provides a single value that represents the average of the dataset.
- In a normal distribution, the data is symmetrically distributed around the mean, which makes the mean the most representative measure of the central value.
- The mean is calculated by summing up all the values in the dataset and dividing by the total number of values. This ensures that the mean reflects both the magnitude and frequency of all data points.
- In a perfectly normal distribution, the mean, median, and mode are all equal. However, the mean is preferred because it utilizes all data points in its calculation, making it statistically more robust.
Explanation of Other Options:
Median
- Rationale: The median is the middle value of a dataset when arranged in ascending or descending order. While it is a good measure of central tendency for skewed distributions, in a normal distribution, it is equivalent to the mean but does not account for the magnitude of all data points.
- It is less sensitive to extreme values (outliers) compared to the mean, but this property is not necessary for a normally distributed dataset, which typically lacks extreme outliers.
Mode
- Rationale: The mode is the value that occurs most frequently in a dataset. While it can be useful for categorical data or unimodal distributions, it is not as informative as the mean in a normal distribution where all values are symmetrically distributed.
- In a normal distribution, the mode is equal to the mean and median, but it provides less insight because it only represents the most frequent value without considering the entire dataset.
Range
- Rationale: The range is the difference between the maximum and minimum values in a dataset. It is not a measure of central tendency; rather, it is a measure of variability or dispersion.
- The range does not provide information about the central value of the dataset and is highly sensitive to extreme values or outliers, making it unsuitable for measuring central tendency.
Conclusion:
- In a normally distributed dataset, the mean is the best measure of central tendency because it incorporates all data points and accurately represents the central value of the dataset. The other measures, while useful in specific contexts, are less appropriate for this scenario.
Education and Research Question 3:
The correlation coefficient in statistics is used to measure:
Answer (Detailed Solution Below)
Option 1 : The relationship between two variables
Education and Research Question 3 Detailed Solution
Correct Answer: The relationship between two variables
Rationale:
- The correlation coefficient is a statistical measure that quantifies the strength and direction of the relationship between two variables. It is denoted by "r" and ranges from -1 to +1.
- A positive correlation (r > 0) indicates that as one variable increases, the other variable also increases. A negative correlation (r
- This measure is widely used in various fields, such as economics, psychology, and biology, to understand the interdependence of two variables and to make predictions based on their relationship.
Additional Information:
- The most common method for calculating the correlation coefficient is Pearson’s correlation coefficient, which measures the linear relationship between two continuous variables.
- Spearman’s rank correlation coefficient can be used to assess non-linear monotonic relationships between variables.
- It is important to note that correlation does not imply causation. A high correlation between two variables does not necessarily mean that one causes the other.
Explanation of Other Options:
The central tendency of the data
- Rationale: This refers to measures like the mean, median, and mode, which summarize the center or typical value of a dataset. It does not address the relationship between two variables.
The frequency distribution of the data
- Rationale: Frequency distribution is a representation of the number of observations within each category or interval of a dataset. It is used to visualize and analyze how data is distributed but does not measure relationships between variables.
The spread of data around the mean
- Rationale: This refers to measures of variability, such as range, variance, and standard deviation, which describe the dispersion of data points around the mean. It does not measure the relationship between two variables.
Conclusion:
- The correlation coefficient is a crucial statistical tool for analyzing and quantifying the relationship between two variables. Understanding its limitations and correct usage ensures meaningful insights and interpretations in data analysis.
Education and Research Question 4:
A rating scale is most commonly used to:
Answer (Detailed Solution Below)
Option 1 : Measure someone's satisfaction or performance
Education and Research Question 4 Detailed Solution
Correct Answer: Measure someone's satisfaction or performance
Rationale:
- A rating scale is a structured method of collecting quantitative data. It is most commonly used to measure subjective experiences like satisfaction, performance, preferences, or attitudes on a defined scale (e.g., 1 to 5, 1 to 10, etc.). This provides a standardized way to evaluate and compare responses across individuals or groups.
- Rating scales are widely employed in surveys, questionnaires, and performance reviews to simplify the process of assessing opinions or outcomes. Examples include Likert scales, numerical scales, and graphical rating scales.
- These scales help organizations and researchers gain insights into how individuals perceive a product, service, or situation, making them essential tools for decision-making and analysis.
Explanation of Other Options:
Collect open-ended responses from participants
- Rationale: Open-ended responses allow participants to freely express their thoughts, ideas, or experiences without restrictions. Unlike rating scales, open-ended questions do not quantify responses on a scale but instead provide qualitative data that requires analysis through coding or thematic interpretation.
- While valuable for gathering detailed insights, open-ended responses are not appropriate for systematically measuring satisfaction or performance.
Collect random feedback from a large group
- Rationale: Random feedback refers to unstructured and spontaneous opinions that are not collected systematically. A rating scale is designed to collect structured and standardized responses, which is the opposite of random feedback.
- Random feedback may lack the consistency and comparability offered by rating scales, making it unsuitable for measuring satisfaction or performance in a formal setting.
Randomly select participants for a study
- Rationale: Random selection is a sampling method used in research to ensure that participants are chosen without bias. This is unrelated to the purpose of a rating scale, which is to collect data from participants about specific attributes or experiences.
- While random selection is an important step in designing a study, it does not involve the use of rating scales.
Conclusion:
- A rating scale is a tool designed to measure subjective aspects like satisfaction, preferences, or performance in a structured and standardized manner. It is distinct from collecting open-ended responses, random feedback, or performing random participant selection, which are unrelated to its primary purpose.
- This method is essential for quantitative analysis in areas like customer satisfaction surveys, employee performance evaluations, and psychological research.
Education and Research Question 5:
Which scale is NOT typically used in measuring psychological or emotional traits?
Answer (Detailed Solution Below)
Option 4 : Measurement scale for physical characteristics
Education and Research Question 5 Detailed Solution
Correct Answer: Measurement scale for physical characteristics
Rationale:
- Psychological and emotional traits are typically measured using scales that capture subjective experiences, attitudes, and perceptions. These scales are specifically designed to quantify complex, abstract traits like emotions, thoughts, or behaviors.
- Measurement scale for physical characteristics, however, is not used for psychological or emotional traits. This type of scale is designed to assess tangible, observable, and measurable physical attributes such as height, weight, or temperature, and does not align with the subjective nature of psychological and emotional assessment.
Explanation of Other Options:
Semantic differential scale
- Rationale: The semantic differential scale is a psychological measurement tool that uses bipolar adjectives (e.g., happy-sad, strong-weak) to gauge people's attitudes, perceptions, or emotional states. It is widely used in psychology, marketing, and sociology to measure subjective traits.
- This scale is highly effective for capturing nuances in emotional and psychological experiences, making it relevant for assessing such traits.
Visual analogue scale
- Rationale: The visual analogue scale (VAS) is a tool used to measure subjective characteristics or feelings that cannot be directly quantified. Typically, respondents mark their level of agreement or intensity of a feeling along a continuous line between two endpoints, such as "no pain" and "worst pain imaginable."
- This scale is frequently used in psychological and emotional assessment, especially in clinical settings for pain or mood evaluation.
Rating scale
- Rationale: Rating scales are commonly used in psychology and emotional assessments to measure the intensity or frequency of behaviors, emotions, or attitudes. Examples include Likert scales, where respondents rate their agreement with statements on a numerical scale (e.g., 1 to 5).
- Rating scales are versatile and widely applied in psychological research and surveys.
Measurement scale for physical characteristics
- Rationale: This type of scale is designed to measure physical attributes such as weight, height, or temperature. It is objective and quantifiable, making it suitable for physical sciences but irrelevant for psychological or emotional traits, which require subjective measurement tools.
- Unlike psychological scales, physical measurement scales cannot capture abstract traits such as emotions, attitudes, or perceptions.
Conclusion:
- Among the given options, the "Measurement scale for physical characteristics" is the correct answer because it is not designed to assess psychological or emotional traits. Instead, it is used for tangible, observable attributes, making it unsuitable for subjective and abstract psychological assessments.
- The other options—semantic differential scale, visual analogue scale, and rating scale—are all valid tools for measuring psychological and emotional traits due to their ability to capture subjective experiences.
Top Education and Research MCQ Objective Questions
A type not research that is undertaken within a defined period of time on a group of people who share common characteristics is called a:
Answer (Detailed Solution Below)
Option 4 : cohort study
Education and Research Question 6 Detailed Solution
Download Solution PDFConcept:
- A cohort study is an observational study.
- It is additional evidence to support the existence of an association of suspected cause and disease.
- A group of people who share common characteristics within a given period of time is a cohort group.
- Types of cohort studies:
- Prospective
- Retrospective
- A combination of prospective and retrospective study
Explanation:
- There are two types of observational study:
- Descriptive study
- Analytical study
- Analytical studies include:
- Ecological or correlational
- Cross-sectional or prevalence
- Case-control or case-reference
- Cohort or follow-up
A method in which several rounds of questions are given to a panel of experts is called:
Answer (Detailed Solution Below)
Option 2 : Delphi technique
Education and Research Question 7 Detailed Solution
Download Solution PDFConcept:
- Delphi technique refers to the process of making decisions by surveying panellists. Several rounds of questionnaires are given to the panel of experts.
- Every panellist is allowed to adjust their answers according to the answers of the last round.
- Delphi's technique involves expert analysis and wisdom of the crowd.
Additional Information
| Meta-analysis | It is a statistical analysis of multiple studies addressing the same research goal. It is an epidemiological study design. |
| Q-sort methodology | It is also known as Q-sort. It involves investigating the perspectives of individuals representing different stances on an issue. |
| Content analysis | It is a tool for qualitative research for content analysis. It is widely used in social research. |
Qualitative and Quantitative Research are the classification of research on the basis of ______
Answer (Detailed Solution Below)
Option 3 : Techniques used
Education and Research Question 8 Detailed Solution
Download Solution PDF
Key Points
A research technique is a systematic plan for conducting research. Research techniques refer to the tools that one uses to do research. These can either be qualitative or quantitative or mixed.
Additional Information
|
Quantitative research |
Qualitative Research |
| Focuses on testing theories and hypotheses. | Focuses on exploring concepts and formulating a theory or hypothesis. |
| Analyzed through math and applied math analysis. | Analyzed by summarizing, categorizing, and decoding. |
| Mainly expressed in numbers, graphs, and tables. | Mainly expressed in words. |
| Requires several respondents. | Requires few respondents. |
| Closed (multiple choice) queries. | Open-ended queries. |
Hence, the correct answer is Techniques used.
Which is called as Non-probability sampling?
Answer (Detailed Solution Below)
Option 4 : Quota sampling
Education and Research Question 9 Detailed Solution
Download Solution PDFConcept:-
- Non-probability sampling is a method of selecting samples for the study when all the samples are not having equal chances to get selected for the study.
Types of Non-Probability sampling are:
- 1. Quota Sampling
- 2. Snowball Sampling
- 3. Judgemental Sampling
- 4. Dimensional Sampling
- 5. Convenience Sampling
Quota sampling:
- In this type of sampling, the researcher chooses the samples as per the study preferences and also segregates the groups to form the quota and start the survey.
- Selection is based on some basic parameters like age, sex, income, etc.
- Field workers are assigned quotas of the number of units satisfying the required characteristics for collecting data
Properties
- When parameters are large, the number of cells increases.
- It misleads if the relevant parameter is omitted.
- In this method, field workers tend to visit respondents who are more likely to be available and accessible.
Additional Information
- The probability Sampling method is also known as the random sampling method. In this method total population has an equal opportunity of being included in the sample. The random sampling method is used in a homogeneous population where the population possesses the same attributes that a researcher is interested in.
- Cluster sampling: it refers to a sampling method wherein the members of the population are selected at random, from naturally occurring groups called clusters.
- Systematic sampling: relies on arranging the target population according to some ordering scheme and then selecting elements at regular intervals through that ordered list.
- Stratified random sampling: it is one in which the population is divided into homogeneous segments, and then the sample is randomly taken from the segments.
Applying an unfair amount of pressure to subjects to complete the responses quickly is called:
Answer (Detailed Solution Below)
Option 3 : Procedural bias
Education and Research Question 10 Detailed Solution
Download Solution PDFOne of the challenges, while doing research is to remain objective and free from biases. Most of your ideas and beliefs are probably linked with certain biases because they are influenced by your opinions or values. A variety of biases have been found to distort people’s impressions of collected data.
Key Points
- Procedural is a type of research bias. It happens when the participants are not given enough time to complete their responses.
- For example:- Employees are asked to fill out the feedback form during lunchtime, they will haphazardly without reading the questions properly. They are under unfair pressure that can affect the validity of their answers.
Thus, it is concluded that Applying an unfair amount of pressure to subjects to complete the responses quickly is called Procedural bias.
Additional Information
- Measurement bias is that bias or a random error that occurs in the collection of the data.
- Inclusion bias is popular in quantitative research and it happens when you select participants to represent your research population while ignoring groups that have alternative experiences.
- Selection bias: Any bias in selecting a group can undermine internal validity. Selection bias indicates the problem that occurs as a result of its existence at the pre-test differences between groups, may interact with the independent variable and thus influence the observed outcome and creates problems; examples would be gender, personality, mental capabilities, and physical abilities, motivation level and willingness to participate.
Sex Education may be introduced at primary stage through
Answer (Detailed Solution Below)
Option 3 : integration with physical education
Education and Research Question 11 Detailed Solution
Download Solution PDFSex education is a part of health education which is essential for healthy living both mentally and physically.
Key Points
Sex education may be introduced at primary stage through integration with physical education because:
- children at this stage are too small to learn the concepts of sex education separately.
- it will help children to learn the basic concepts of physical and sexual changes in an integrated manner.
- physical education is also a part of health education which emphasizes to improve physical and mental fitness.
Hence, it could be concluded that sex education may be introduced at primary stage through integration with physical education.
What is a component of in-service education?
Answer (Detailed Solution Below)
Option 2 : Staff development program
Education and Research Question 12 Detailed Solution
Download Solution PDFConcept:-
- In service, education is the Planned learning experience rendered by the employing agency for its employees. As Nursing is a dynamic profession that is subject to rapid change in health care protocols, in-service education plays an important role in Quality Nursing Care.
Types of In-service Education:
- Workshops
- Demonstrations or Hand on Practice Sessions
- Lectures
Components of In services Education
- Staff Development Programs: It helps to meet the educational needs of the Nursing staff which helps in delivering Evidence-based care to the patients.
- Scope of In-Service Education in nursing practice is very significant and nurses are committed to long-life, learning practice and it needs to be continued throughout the professional life.
- If the nurses lack motivation in Learning the new concepts and practices they will continue the practicing of old trends which are to be changed as per the social needs and scientific advancements.
Additional Information
How we learn Auditory, Visual and Kinesthetic
- We remember 1% through taste, 10% of what we read, 1.5% of what we touch, 20% of what we hear, 3.5% of what we smell, 30% of what we see, and 80% of what we say, and what we react.
The process of selecting a subset of population for a survey is called as
Answer (Detailed Solution Below)
Option 1 : Sampling
Education and Research Question 13 Detailed Solution
Download Solution PDFConcept:-
- Sampling: the process of selecting a small number of elements from a larger defined target group of elements
- The information gathered from the small group will allow judgments to be made about the larger groups
Types of sampling:
|
Simple random sampling |
Sample selected at random from a population in which every member of the population has an equal chance of being selected. |
|
Systematic random sampling |
Selecting every nth case from a population |
|
Stratified random sampling |
Randomly selecting participants for a sample from predetermined strata in a population. |
|
Cluster sampling |
Selecting a sample based on pre-organized groups |
|
Convenience sampling |
Selecting a sample from whatever subjects are available |
Additional Information
- Triangulation: Triangulation is an approach to research that uses a combination of more than one research strategy in a single investigation.
- Random Allocation: the participants in the study population are randomly allocated into two groups using random number tables, or computers to avoid selection and confounding biases.
Which among the following is a type of Non probability sampling?
Answer (Detailed Solution Below)
Option 3 : Purposive sampling
Education and Research Question 14 Detailed Solution
Download Solution PDFConcept:
- Sampling is a process of selecting predetermined number of observations from a larger population
- Majorly we have 2 types probability and non probability sampling techniques
- Probability sampling technique includes
- Simple random sampling
- Cluster random sampling
- Systematic random sampling
- Stratified random sampling
- Non probability sampling technique includes
- Convenience sampling
- Judgmental or purposive sampling
- Snowball sampling
- Quota sampling
Additional Information
- In probability sampling all the members will have an equal opportunity to participate in research
- In non probability sampling researcher selects the samples randomly where all the participants may not get equal chance to participate in study
- Systematic sampling in this the researcher chooses the sample members of a population at regular intervals
- In stratified random sampling the researcher divides the population into small groups which represents the larger group
- Purposive sampling method researcher purely consider the purpose of the study along with the understanding of audience
The main characteristics of scientific research is _____
Answer (Detailed Solution Below)
Option 3 : Empirical Research
Education and Research Question 15 Detailed Solution
Download Solution PDFConcept:-
Scientific research:
- it is a social institution and a way to produce knowledge.
- The main characteristic of scientific research is Empirical research.
- Its characteristics would be that it is based on observable and measurable evidence. It directly engages with the material world, rather than relying on the theoretical or conceptual aspects alone.
- Scientific research is a way of gathering data and harnessing curiosity. This research provides scientific information and theories for the explanation of nature and the properties of the world. It makes practical applications possible.
- It is a body of techniques for investigating phenomena, acquiring new knowledge, or correcting and integrating previous knowledge. To be termed scientific, a method of inquiry is commonly based on empirical or measurable evidence subject to specific principles of reasoning.
- It is to be understood as forming a sequence of discrete stages that moves the researcher from a position of ignorance to one of greater knowledge.
Explanation:
- Experimental research: it is a scientific investigation that sets out to determine the cause and effect of two or more variables.
- It includes a hypothesis, a variable that can be manipulated by the researcher, and variables that can be measured, calculated, and compared.