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MPC-005: Research Methods in Psychology

MPC-005: Research Methods in Psychology

IGNOU Solved Assignment Solution for 2023-24

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Assignment Code: MPC-005/TMA/2023-24

Course Code: MPC-005

Assignment Name: Research Methods

Year: 2023-2024

Verification Status: Verified by Professor


Answer the following questions in 1000 words each. 3 x 15 = 45 marks

Q1) Define sampling. Discuss the different methods of sampling.

Ans) The selection of a subset of items from a broader population for the purpose of representing and studying is an essential component of research, and it is referred to as sampling. Due to the fact that it enables researchers to draw conclusions about a population based on the analysis of a smaller, more manageable sample, this technique is essential in a variety of sectors, including the social sciences, market research, and scientific investigations.

It is possible for the selection of the sampling procedure to have a considerable impact on the validity and generalizability of the findings of the study. There are a number of approaches, each of which has a unique set of benefits and drawbacks.

Random Sampling:

  1. Definition: A random sampling method ensures that every individual in the population has an equal opportunity of being chosen for the sample. The objective of this approach is to reduce bias and guarantee that the sample is a representation of the population that is representative of the whole.

  2. Procedure: For the purpose of selecting participants, researchers may make use of random number generators, lottery systems, or any number of other randomization procedures. When working with big populations that are comprised of a varied range of people, this strategy is quite helpful.

  3. Advantages: The elimination of selection bias through the use of random sampling makes it possible to generalise findings to the entire population.

  4. Limitations: There are several circumstances in which it might be impracticable or even impossible to put into practise, particularly when there are few resources available or when the population is not well defined.

Stratified Sampling:

  1. Definition: In stratified sampling, the population is divided into subgroups or strata based on certain characteristics (such as age, gender, or socioeconomic status), and then random samples are drawn from each stratum.

  2. Procedure: Researchers identify strata, determine the proportion of each stratum in the population, and then randomly select samples from each stratum accordingly.

  3. Advantages: This ensures that all relevant subgroups are represented, in order to provide a more accurate depiction of the diversity that exists within the population.

  4. Limitations: Requires detailed information about the population to create appropriate strata, and it may be more complex to implement than random sampling.

Systematic Sampling:

  1. Definition: After selecting a beginning point at random, systematic sampling comprises selecting every kth element from a list by means of a selection process. The "k" value is determined by dividing the entire population size by the sample size that is wanted within the population.

  2. Procedure: After selecting a random starting point, every kth element is included in the sample until the required sample size is achieved.

  3. Advantages: A strategy that is uncomplicated and efficient, particularly within circumstances in which a complete list of the population is available.

  4. Limitations: Vulnerable to periodic patterns in the population list, potentially introducing bias if there's a hidden order in the arrangement.

Cluster Sampling:

  1. Definition: During the process of cluster sampling, the population is first segmented into clusters, and then a comprehensive selection of clusters is done at random. After that, the researcher begins to investigate each individual member of the selected clusters.

  2. Procedure: Clusters are chosen at random, and all of the individuals that are contained within the clusters that are chosen are included in the sample distribution.

  3. Advantages: Cost-effective when dealing with large and geographically dispersed populations. It is also less time-consuming.

  4. Limitations: If the clusters are not homogenous, this could result in the introduction of bias, and the conclusions could not be as precise as they would be with other methods.

Convenience Sampling:

  1. Definition: The method of selecting participants for convenience sampling entails selecting them based on their availability and how easily they can be reached by the researcher.

  2. Procedure: Researchers choose participants who are convenient to reach or readily available, such as volunteers or individuals easily accessible.

  3. Advantages: Quick and cost-effective, especially for exploratory studies or when time and resources are limited.

  4. Limitations: Excessively prone to selection bias due to the possibility that the sample may not accurately represent the larger population. Some of the findings might not be generalizable.

Quota Sampling:

  1. Definition: In quota sampling, individuals are chosen to meet predetermined quotas based on particular criteria, such as age, gender, or ethnicity. Quota sampling is becoming increasingly popular.

  2. Procedure: The researchers will first establish quotas for each subgroup, and then they will select volunteers who fulfil those quotas. This process will continue until the specific sample size that they have identified is reached.

  3. Advantages: Allows for control over the composition of the sample, ensuring representation from specific demographic groups.

  4. Limitations: Similar to convenience sampling, there is a risk of bias, as the researcher may consciously or unconsciously select individuals who fit the predetermined quotas.

Purposive Sampling:

  1. Definition: Also known as judgmental or selective sampling, purposive sampling involves deliberately selecting participants who possess specific characteristics relevant to the research question.

  2. Procedure: When it comes to selecting volunteers for the study, researchers rely on their own experience, competence, or other distinctive characteristics that are relevant to the investigation.

  3. Advantages: Useful when seeking information from specific individuals who have particular knowledge or experiences.

  4. Limitations: Due to the fact that the selection process is subjective and depends on the judgement of the researcher, it is susceptible to researcher bias.

Snowball Sampling:

  1. Definition: Snowball sampling relies on existing participants to recruit additional participants. This method is often used when studying hard-to-reach populations.

  2. Procedure: Initially, a small group of participants is identified and interviewed. These participants then refer the researcher to others who meet the study criteria, creating a "snowball" effect.

  3. Advantages: When conducting research on communities who are hidden or marginalised, where typical sampling methods may present difficulties, this strategy is useful.

  4. Limitations: There is a possibility that the findings cannot be generalised because the sample is dependent on referrals and may not be representative of the overall population.

Q2) Discuss the steps involved in research process.

Ans) In order to examine a specific subject, provide a solution to a research question, or make a contribution to the body of information that already exists, researchers take a sequence of processes that are ordered and methodical in approach. There is a possibility that the specific procedures will differ significantly depending on the field of study and the type of the research being conducted; however, the following broad framework will define the most important stages of the research process.

  1. Identifying the Research Problem:

    Definition: The first thing that has to be done is to identify and specify the research topic or question that the study intends to answer. At this stage, it is necessary to have a comprehensive understanding of the subject matter, its significance, and any potential knowledge gaps that may occur.


    a) To gain an understanding of the present state of knowledge, review the relevant literature.

    b) Locate any voids, conflicts, or questionable regions that require additional investigation.

    c) The formulation of a research topic or hypothesis that is specific and targeted is required.

  2. Review of Literature:

    Definition: Carrying out an exhaustive review of the existing literature on the subject that has been selected in order to gain an understanding of what is already known, to recognise important concepts, theories, and methodologies, and to contextualise the research within the context of the larger academic discourse.


    a) Conduct research and analysis on scholarly publications, books, and any other materials that are pertinent.

    b) Briefly summarise the most important results, hypotheses, and approaches.

    c) Locate any areas that require additional research, as well as any gaps or contradictions that may exist.

  3. Formulating a Hypothesis or Research Question:

    Definition: Based on the identified research problem and the literature review, researchers formulate a hypothesis (for quantitative studies) or a research question (for qualitative studies) that guides the investigation.


    a) Create a statement that is both clear and able to be tested, known as a hypothesis, or a query that is focused.

    b) Making sure that the research problem and the relevant literature are aligned is important.

  4. Designing the Research:

    Definition: During this stage, one will be responsible for planning the overall research design, which includes the type of study (experimental, observational, survey, or case study), the methods of data collecting, and the sampling strategy.


    a) Choose the research design that best fits the research question and objectives.

    b) Select appropriate data collection methods (surveys, interviews, experiments).

    c) Determine the sampling method (random, stratified, convenience).

  5. Collecting Data:

    Definition: The process of carrying out the research plan that has been created in order to collect information or data that is pertinent to the research topic or hypothesis.


    a) Make use of methods such as conducting interviews, conducting surveys, conducting experiments or observing behaviours.

    b) Take measures to ensure that the techniques for data collecting are in line with the research design.

    c) In addition to documenting the data, one should keep a systematic record of it.

  6. Analysing Data:

    Definition: Following the completion of the data collection process, the researchers make use of relevant statistical or qualitative methodologies to analyse the information in order to draw conclusions and provide a response to the research question.


    a) Use statistical software for quantitative analysis or thematic analysis for qualitative data.

    b) Interpret findings in the context of the research question and existing literature.

    c) Determine whether there are any major discrepancies, patterns, trends, or correlations at play.

  7. Interpreting Results:

    Definition: As part of this step, one will draw conclusions based on the analysis of the data and determine the implications of the findings for the field of study as a whole.


    a) Establish a connection between the findings and the research question or hypothesis.

    b) Discuss the significance of the findings and their practical or theoretical implications.

    c) Take into consideration the study's limitations as well as any possible biases.

  8. Drawing Conclusions and Generalizing Results:

    Definition: Researchers develop inferences and evaluate the extent to which their findings can be generalised to a larger population or theory based on their interpretation of the outcomes of their respective studies.


    a) The extent to which the findings can be extended to different contexts or people should be thoroughly discussed.

    b) Take into account any restrictions that might have an impact on the results' capacity to be generalised.

    c) Make suggestions for any future study or practical applications that could benefit from them.

  9. Communicating Results:

    Definition: In order to disseminate the findings of the research, a number of different communication channels are being utilised. These channels include academic articles, conferences, reports, and presentations.


    a) Compose a research paper or thesis that provides a summary of the study, including the methodology, findings, and opinions.

    b) In preparation for professional meetings or academic conferences, one should prepare visual aids or complete presentations.

    c) It is important to communicate the findings to the appropriate stakeholders, policymakers, or the general public.

  10. Reflecting and Iterating:

Definition: After the research has been completed, the researchers will have the opportunity to reflect on the process, identify the lessons that were learnt, and discuss prospective areas that could be improved or further explored.


a) Consider some of the difficulties encountered throughout the study process.

b) Take into consideration the consequences of the limitations of the study.

c) Determine whether there are any possibilities for additional research or modifications to the research design.

Since the research process is iterative, it is possible for researchers to return to particular steps in order to include new insights, feedback, or findings that were not anticipated. It is essential for researchers to uphold ethical norms throughout the entire process. This includes protecting the well-being of participants, truthfully reporting techniques and results, and showing respect for the intellectual property of others.

An organised approach to inquiry is provided by the methodical character of the research process, which helps to stimulate the development of new information and contributes to the advancement of academic fields as well as practical applications.

Q3) Discuss the meaning, types and relevance of qualitative research. Explain the ethical guidelines in qualitative research.

Ans) The methodological approach known as qualitative research is centred on the goal of comprehending and interpreting the intricate nature of human experiences, behaviours, and occurrences. Discovering meaning and gaining rich, in-depth insights are the goals of this approach, which is defined by an all-encompassing and context-dependent investigation of the contemporary social reality.

In contrast to quantitative research, which places a greater emphasis on numerical data and statistical analysis, qualitative research makes use of non-numerical data, such as words, images, or narratives, in order to capture the intricacies of social phenomena.

Types of Qualitative Research:


  1. Description: Within a particular community or cultural group, ethnography entails conducting fieldwork that is both in-depth and extended in duration. The researchers want to gain an understanding of the routines, social dynamics, and daily lives of the group that is being examined.

  2. Relevance: The field of ethnography offers a comprehensive viewpoint on social practises and cultural practises, making it possible to investigate the meanings and behaviours that are shared by a group of people.


  1. Description: Phenomenology is an academic discipline that aims to investigate and describe the lived experiences of humans in relation to a specific topic. The objective of the researchers is to gain an understanding of the core of these experiences as well as the interpretations that individuals ascribe to them.

  2. Relevance: The field of phenomenology is extremely useful since it allows for the discovery of the subjective viewpoints of individuals, which in turn contributes to a more profound comprehension of their feelings and perceptions.

Grounded Theory:

  1. Description: This inductive method is known as grounded theory, and its primary objective is to generate ideas that are founded on the evidence itself. Researchers do data analysis in a methodical manner in order to recognise patterns, categories, and themes, which are subsequently utilised in the process of developing new hypotheses.

  2. Relevance: The application of grounded theory is very helpful when it comes to investigating intricate social processes and building explanation frameworks that are founded on actual facts.

Case Study:

  1. Description: Performing a comprehensive investigation of a particular person, group, organisation, or phenomenon is what is meant by the term "case study." A wide variety of sources, including interviews, observations, and documents, are utilised by researchers in order to get more specific information.

  2. Relevance: When it comes to investigating unusual or uncommon cases, case studies are quite helpful because they offer a comprehensive narrative that can either serve as an illustration or as a foundation for additional investigation.

Narrative Research:

  1. Description: Research that is based on narratives involves the collection and analysis of personal narratives or stories that are shared by individuals. For the purpose of gaining an understanding of how individuals manufacture meaning, researchers investigate the structure, content, and context of these fictional narratives.

  2. Relevance: When it comes to investigating personal experiences, the construction of identities, and the ways in which individuals understand and convey their tales, narrative research is particularly effective.

Relevance of Qualitative Research:

  1. In-Depth Understanding: Qualitative research allows researchers to explore complex social phenomena in depth, capturing the richness and nuances of human experiences that quantitative methods may overlook.

  2. Contextual Insights: The emphasis on context in qualitative research enables a more comprehensive understanding of social phenomena within their natural settings, providing insights into the cultural, historical, and social contexts.

  3. Theory Generation: Qualitative research is often used to generate new theories or refine existing ones. Grounded theory, in particular, allows researchers to develop theoretical frameworks based on empirical evidence.

  4. Flexibility: Qualitative methods are flexible, allowing researchers to adapt their approaches during the research process. This flexibility is beneficial when exploring dynamic and evolving phenomena.

  5. Participant Perspectives: Qualitative research prioritizes the voices of participants, ensuring that their perspectives and interpretations are central to the study. This participant-centric approach adds depth and authenticity to the findings.

Ethical Guidelines in Qualitative Research:

  1. Informed Consent: Researchers must clearly explain the purpose, procedures, and potential risks and benefits of the study to participants. Informed consent is an ongoing process, and participants have the right to withdraw at any time without facing consequences.

  2. Confidentiality: Researchers should protect the confidentiality of participants by avoiding the disclosure of personally identifiable information. This includes ensuring anonymity in reporting and storing data securely.

  3. Voluntary Participation: Participation in qualitative research should be voluntary, and individuals should not be coerced or unduly influenced to take part. Researchers must respect participants' autonomy and right to decline or withdraw from the study.

  4. Beneficence and Non-Maleficence: Researchers should strive to maximize benefits and minimize harm to participants. This involves considering the potential impact of the research on participants' well-being and taking steps to mitigate any negative consequences.

  5. Transparent Researcher Roles: Researchers should be transparent about their roles and affiliations, avoiding any deception that could compromise the trust of participants. Honest and open communication helps maintain the integrity of the research process.

  6. Debriefing: After data collection, researchers should provide participants with a debriefing session, offering additional information about the study and addressing any questions or concerns. This helps ensure that participants leave the study with a clear understanding of their involvement.

  7. Cultural Sensitivity: Researchers must be culturally sensitive and respectful of the cultural norms and practices of the participants. This includes recognizing and addressing power dynamics, avoiding cultural stereotypes, and seeking guidance from cultural experts when necessary.

  8. Researcher Reflexivity: Researchers should engage in reflexivity, acknowledging their own biases, assumptions, and potential impact on the research. Transparent reporting of the researcher's background and reflexivity enhances the credibility of the study.

  9. Approval from Ethical Review Boards: Researchers should seek approval from ethical review boards or Institutional Review Boards (IRBs) before initiating the study. Ethical review ensures that research plans align with ethical standards and safeguard the rights and well-being of participants.

  10. Honest Reporting: Researchers should accurately and honestly report their findings, including any limitations or challenges encountered during the research process. Transparent reporting contributes to the credibility and trustworthiness of the study.


Answer the following questions in 400 words each. 5 x 5 = 25 marks

Q4) Criteria and misconceptions of case studies.

Ans) In-depth Exploration:

a) Criterion: Case studies detail a case or series. Research aims to understand the subject's complexities, conditions, and dynamics.

b) Importance: Case studies let academics examine subtle intricacies and unique case aspects in greater detail than other research methodologies.

Contextual Analysis:

a) Criterion: Case studies emphasise studying events in nature. The study examines how historical, cultural, and organisational aspects affect the situation.

b) Importance: Understanding the context helps researchers discover the case's interrelated relationships and comprehend the findings holistically.

Rich Data Collection:

a) Criterion: Case studies acquire rich and diverse data from interviews, observations, documents, and historical records. The study is more credible with more data points.

b) Importance: Comprehensive data collection enables researchers to triangulate information, validate findings, and capture the multifaceted nature of the case.

Holistic Perspective:

a) Criterion: The case under investigation is examined holistically in case studies. This entails studying individual, organisational, and systemic factors.

b) Importance: A holistic approach ensures that researchers do not oversimplify complex phenomena and encourages a nuanced understanding of the interactions within the case.

Longitudinal Analysis:

a) Criterion: Some case studies involve longitudinal analysis, tracing developments and changes over time. This temporal dimension allows researchers to capture the evolution of the case and identify patterns or trends.

b) Importance: Longitudinal analysis contributes to a dynamic understanding of the case, offering insights into the temporal aspects of behaviour, decision-making, and organizational evolution.

Misconceptions of Case Studies:


a) Misconception: A prevalent misperception is that case study findings may be applied to larger groups. Direct generalisation is difficult since case studies focus on individual, often unique cases.

b) Clarification: Case studies are context-specific, and while they provide rich insights, caution is needed when applying findings to other settings. The emphasis is on depth rather than breadth.

Subjectivity and Bias:

a) Misconception: Some critics argue that case studies are inherently subjective and prone to researcher bias. This misconception arises from the qualitative nature of case study research.

b) Clarification: To reduce bias, rigorous case study research requires reflexivity, transparency, and triangulation. Case studies can improve reliability and validity by including the researcher's perspective and multiple data sources.

Lack of Rigor:

a) Misconception: Critics may view case studies as less rigorous than quantitative research. Because case study design is flexible, this misperception exists.

b) Clarification: Systematic data analysis improves case studies. Ethics, transparency, and research design ensure rigour.

Limited Generalizability:

a) Misconception: Some say case studies' small sample sizes hinder generalizability.

b) Clarification: Case studies strive for transferability, not statistical generalizability. A well-conducted case study might inform similar circumstances or inspire relevant research.

Q5) Types of variables.

Ans) In research, variables are characteristics or attributes that can vary and are subject to measurement or manipulation. Understanding the different types of variables is essential for designing and conducting studies.

  1. Independent Variables:

    Definition: Independent variables are the variables that are manipulated or controlled by the researcher. They are the presumed causes or antecedents in a study. In an experiment investigating the effect of different teaching methods on student performance, the teaching methods would be the independent variable.

  2. Dependent Variables:

    Definition: Dependent variables are the outcomes or responses that are measured to assess the impact of the independent variable. They are the variables that depend on the changes in the independent variable. In the same teaching methods experiment, student performance or test scores would be the dependent variable.

  3. Control Variables:

    Definition: Control variables are factors that the researcher holds constant or controls to prevent them from confounding the relationship between the independent and dependent variables. In a study on the impact of a new drug on blood pressure, factors like age, diet, and exercise could be controlled to isolate the drug's effects.

  4. Categorical Variables:

    Definition: Categorical variables are qualitative variables that represent categories or groups. They can be nominal (categories with no inherent order) or ordinal (categories with a meaningful order). Gender (male, female) is a nominal categorical variable, while educational attainment (high school, college, graduate) is an ordinal categorical variable.

  5. Continuous Variables:

    Definition: Continuous variables are quantitative variables that can take on any value within a given range. They are measured using numerical values. Age, height, weight, and temperature are examples of continuous variables.

  6. Discrete Variables:

    Definition: Discrete variables are quantitative variables that can only take on specific, distinct values, often counted in whole numbers. The number of siblings, the number of cars in a parking lot, and the number of items purchased are examples of discrete variables.

  7. Moderator Variables:

    Definition: Moderator variables influence the strength or direction of the relationship between the independent and dependent variables. They help identify conditions under which the relationship may vary. In a study on the relationship between sleep and memory, age could be a moderator variable.

  8. Mediator Variables:

    Definition: Mediator variables explain the process or mechanism through which the independent variable affects the dependent variable. They help understand the underlying causal pathways. In a study on the impact of exercise on mental health, improved self-esteem could be a mediator variable.

Q6) Advantages and disadvantages of quasi experimental design.

Ans) There are some parallels between experimental designs and quasi-experimental designs; however, quasi-experimental designs do not include full randomization. This makes them acceptable for situations in which random assignment of individuals to groups would be undesirable or unethical.


  1. Real-World Applicability: Quasi-experimental designs are often more applicable in real-world settings, where random assignment is challenging or unethical. Researchers can study phenomena as they naturally occur, increasing the external validity of the findings.

  2. Ethical Considerations: In situations where, random assignment is impractical or impossible, quasi-experimental designs provide an ethical alternative. It is still possible for researchers to explore cause-and-effect relationships regardless of whether or not specific factors are manipulated.

  3. Naturalistic Observation: Quasi-experimental designs allow for the observation of behaviour in naturalistic settings, providing insights into real-world situations. This is particularly valuable when studying complex, dynamic, or socially sensitive phenomena.

  4. Feasibility: Compared to actual experimental designs, quasi-experimental designs are frequently more viable and cost-effective methods of research. It is possible to carry them out in real-world settings with less disruption, and they require fewer resources to carry out.


  1. Lack of Randomization: The primary limitation of quasi-experimental designs is the absence of randomization. Without random assignment, establishing causation becomes more challenging, as researchers cannot be certain that observed differences are due to the manipulated variable.

  2. Threats to Internal Validity: Quasi-experimental designs are more susceptible to threats to internal validity, such as selection bias, maturation, and history. These threats can introduce confounding variables and compromise the ability to draw causal inferences.

  3. Difficulty Establishing Causation: It is more challenging to demonstrate a cause-and-effect link when using quasi-experimental designs since these designs do not undergo the same level of rigorous control as real experimental designs. It is possible that the interpretation of the data will be clouded by confounding variables and alternative hypotheses.

  4. Limited Control Over Extraneous Variables: It is more difficult for researchers to exert control over extraneous variables that could potentially affect the results of the investigation. Because of this lack of control, the certainty of the causal links between the variables that are independent and those that are dependent can be reduced.

  5. Difficulty in Replication: It may be difficult to repeat quasi-experimental designs, particularly those that were carried out in situations that were either entirely unique or very specific. Because of this, it may be more difficult to verify if the findings can be generalised to a variety of settings.

Q7) Types of questions that can be used in a survey research.

Ans) Survey research collects data from individuals using standardised questionnaires or interviews. Survey questions are vital for gathering relevant and reliable data.

Closed-Ended Questions:

a) Definition: These questions offer multiple-choice or Likert scale answers.

b) Example: "On a scale from 1 to 5, how satisfied are you with our product?"

c) Purpose: Closed-ended questions are easy to analyse and quantify, making them suitable for obtaining structured and measurable data.

Open-Ended Questions:

a) Definition: Open-ended questions allow for comprehensive, freely-worded responses.

b) Example: "What suggestions do you have for improving our services?"

c) Purpose: Open-ended questions offer insights into participants' thoughts, opinions, and ideas, providing qualitative data.

Multiple-Choice Questions:

a) Definition: Respondents choose from a list of predefined options.

b) Example: "Which of the following factors influenced your purchase decision? (a) Price, (b) Quality, (c) Brand reputation."

c) Purpose: Multiple-choice questions are effective for categorizing responses and facilitating data analysis.

Likert Scale Questions:

a) Definition: Survey respondents rate their agreement or disagreement with a statement.

b) Example: "Please rate your agreement with the following statement: 'The customer service was helpful.' (Strongly Disagree, Disagree, Neutral, Agree, Strongly Agree)"

c) Purpose: Likert scales measure attitudes or opinions on a continuum, providing a quantitative measure.

Semantic Differential Scale Questions:

a) Definition: Respondents rate an object, concept, or experience on opposite adjectival pairs.

b) Example: "Rate your experience with our website: (Easy to navigate – Difficult to navigate)"

c) Purpose: Semantic differential scales capture perceptions and attitudes with bipolar adjectives.

Ranking Questions:

a) Definition: Respondents prioritize or rank a set of options based on their preferences.

b) Example: "Please rank the following features in order of importance to you."

c) Purpose: Ranking questions help identify the relative importance or preferences among a set of items.

Matrix Questions:

a) Definition: Matrix questions present a series of related questions with a common set of response options.

b) Example: "Please rate your satisfaction with the following aspects of our service: (a) Communication, (b) Timeliness, (c) Quality)"

c) Purpose: Matrix questions streamline the survey, making it more user-friendly while addressing multiple aspects.

Demographic Questions:

a) Definition: Questions that collect information about respondents' demographic characteristics.

b) Example: "What is your age, gender, and level of education?"

c) Purpose: Demographic questions help classify and segment respondents based on key demographic variables.

Behavioural Intention Questions:

a) Definition: Questions that explore respondents' intentions or planned behaviours.

b) Example: "Do you intend to purchase our product in the next six months?"

c) Purpose: Behavioural intention questions assess future actions or decisions.

Q8) Types of correlational research design.

Ans) Correlational research designs examine the relationship between two or more variables without manipulating them. These designs help researchers understand the degree and direction of association between variables.

  1. Cross-Sectional Correlational Design:

    a) Definition: This design examines variable correlations using single-point participant data.

    b) Example: Comparing exam scores and study hours among a set of students at a certain time.

    c) Purpose: To identify variable correlations at a given time, revealing probable relationships.

  2. Longitudinal Correlational Design:

    a) Definition: This design involves collecting data from the same participants over an extended period to examine changes and correlations over time.

    b) Example: Investigating the correlation between annual income and job satisfaction over a five-year period.

    c) Purpose: To explore how variables change and whether correlations remain consistent or evolve over time.

  3. Retrospective or Ex Post Facto Correlational Design:

    a) Definition: Researchers examine the relationship between variables by analysing existing data or events that have already occurred.

    b) Example: Investigating the correlation between childhood experiences and current mental health by examining historical records or retrospective self-reports.

    c) Purpose: To explore associations between variables after they have naturally occurred, without direct manipulation.

  4. Bidirectional Correlational Design:

    a) Definition: This design examines the correlation between two variables while considering that each variable may influence the other.

    b) Example: Exploring the correlation between physical activity and mental health, acknowledging that increased physical activity may positively impact mental health, and improved mental health may lead to more physical activity.

    c) Purpose: To understand the reciprocal relationship between variables.

  5. Moderated Correlational Design:

    a) Definition: Researchers investigate whether the strength or direction of the correlation between two variables is influenced by a third variable (the moderator).

    b) Example: Studying the correlation between study hours and academic performance, considering whether the presence of a learning support program moderates this relationship.

    c) Purpose: To identify conditions under which the correlation between variables may vary.

  6. Mediated Correlational Design:

    a) Definition: In this design, researchers examine the underlying mechanism or process (mediator) through which one variable influences another.

    b) Example: Investigating the correlation between job autonomy and job satisfaction, with perceived job meaningfulness as a mediator.

    c) Purpose: To understand the processes that explain why and how a correlation between two variables occurs.

  7. Partial Correlational Design:

    a) Definition: Researchers examine the relationship between two variables while statistically controlling for the influence of a third variable.

    b) Example: Investigating the correlation between sleep duration and academic performance while controlling for the effect of socioeconomic status.

    c) Purpose: To isolate and understand the unique association between two variables after accounting for the impact of a third variable.


Answer the following questions in 50 words each. 10 x 3 = 30 marks

Q9) Difference between causal comparative and experimental research design.

Ans) Difference between causal comparative and experimental research design are:

Q10) Types of hypotheses.

Ans) Types of hypotheses:

  1. Research Hypothesis: Predicts a relationship or difference between variables.

  2. Null Hypothesis: States no significant relationship or difference between variables.

  3. Directional Hypothesis: Predicts the direction of the relationship or difference.

  4. Nondirectional Hypothesis: Predicts the existence of a relationship or difference without specifying its direction.

Q11) Types of Validity.

Ans) Types of Validity are:

  1. Content Validity: Ensures the adequacy of test content.

  2. Construct Validity: Assesses the accuracy of measuring theoretical constructs.

  3. Criterion-Related Validity: Examines the correlation with established criteria.

  4. Concurrent Validity: Assesses the relationship between a new measure and an existing one administered at the same time.

  5. Predictive Validity: Predicts future performance based on current measures.

Q12) Reliability.

Ans) Reliability refers to the consistency, stability, or dependability of a measurement. It assesses the extent to which a test or measurement produces consistent results under consistent conditions over time. Types of reliability include test-retest reliability (consistency across repeated measurements), inter-rater reliability (consistency across different raters), and internal consistency (consistency within a test).

Q13) Types of survey research.

Ans) Types of survey research are:

  1. Cross-Sectional Surveys: Collect data at a single point in time.

  2. Longitudinal Surveys: Gather data from the same participants over an extended period.

  3. Panel Surveys: Follow the same sample over multiple waves of data collection.

  4. Trend Studies: Examine changes in a variable across different populations over time.

  5. Cohort Studies: Track specific groups over time.

Q14) Quantitative research design.

Ans) Quantitative research designs employ systematic methods to collect and analyse numerical data. Common designs include experimental (manipulating variables for causal inference), correlational (examining relationships between variables), and descriptive (summarizing and interpreting data) designs. Quantitative research typically employs methodologies such as surveys, experiments, and observational studies, with an emphasis on statistical analysis for any findings that are obtained.

Q15) Factorial Design.

Ans) A factorial design is a research design that involves the simultaneous manipulation of two or more independent variables, allowing researchers to explore the effects of multiple factors on the dependent variable. It provides insights into the main effects of each variable as well as potential interactions between them, enhancing experimental understanding.

Q16) Definition of research design.

Ans) Research design refers to the overall structure and plan of a study, outlining the procedures for collecting, analysing, and interpreting data. It includes the choice of research methods, sampling techniques, data collection tools, and strategies for data analysis. The validity, reliability, and generalizability of the study are all ensured by a research plan that has been carefully designed.

Q17) Field experiment.

Ans) A field experiment is a research study conducted in a real-world setting outside a controlled laboratory environment. Researchers manipulate independent variables to observe their effects on participants' behaviour, responses, or outcomes. Field experiments offer high external validity, providing insights into real-life situations while introducing some challenges in controlling extraneous variables compared to lab experiments.

Q18) Research Biases.

Ans) Research biases are systematic errors or distortions in the collection, analysis, interpretation, or publication of research data. Confirmation bias, also known as favouring information, that serves to support preexisting opinions, selection bias, which refers to systematic disparities in groups that are being compared, and publication bias are all examples of common types of bias (favouring the publication of positive results over negative or neutral findings).

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