ANSWERS 👉 1-5 6-10 11-17 18-27 NUMERICAL QUESTIONS
Q11. Explain Grounded Theory: steps, types of coding, and its relevance in psychology.(10 Marks — Very frequently repeated)
Answer
1. Introduction
Grounded Theory (GT) is one of the most important qualitative research methods used in psychology and social sciences.
Developed by Glaser and Strauss (1967), it focuses on generating theory from data, rather than testing existing theories.
Unlike traditional research (which begins with a hypothesis), grounded theory begins with data collection and ends with a theory grounded in real-world observations.
2. Meaning / Definition of Grounded Theory
Grounded Theory is a systematic, inductive qualitative method in which theories are built bottom-up from the data collected from participants.
Simple definition:
👉 Grounded Theory = A theory developed from data, not imposed on data.
It is useful when existing theories do not explain a phenomenon adequately.
3. Purpose of Grounded Theory
- To discover patterns in social or psychological processes
- To build new theoretical explanations
- To understand complex lived experiences
- To study problems with little prior research
4. Steps in Grounded Theory
Grounded Theory follows a cyclical, systematic set of procedures:
Step 1: Data Collection
Data are collected through:
- Interviews
- Observations
- Focus groups
- Documents
Open-ended methods are preferred.
Step 2: Open Coding
- The data are broken down into small units.
- Concepts are identified and labelled.
- The researcher asks:
“What is happening in the data?”
Example:
From interview data about stress, codes may include:
"pressure," "overthinking," "lack of sleep," "deadlines."
Step 3: Axial Coding
- Codes are grouped into categories based on relationships.
- The goal is to link categories with subcategories.
Example:
Category: Sources of Stress
Subcategories: work load, peer pressure, family expectations.
Step 4: Selective Coding
- The core category is identified.
- Theory is integrated around this central theme.
Example:
Core category: “Perceived lack of control.”
This central category ties all other categories together.
Step 5: Constant Comparative Method
Throughout the process:
- New data are compared with existing codes
- Concepts evolve
- Categories become refined
This ensures the theory is deep and grounded.
Step 6: Theoretical Saturation
This stage is reached when:
- No new categories emerge
- Data become repetitive
- Additional interviews provide no new insights
Only then is the theory complete.
Step 7: Development of Theory
Finally, the researcher constructs a theory that:
- Explains the relationships between categories
- Emerges entirely from participant data
- Describes the psychological or social process studied
This is the final outcome of Grounded Theory.
5. Types of Coding in Grounded Theory
Grounded Theory uses three main types of coding:
A. Open Coding
- Initial, line-by-line coding
- Identifying meaningful units
- Breaking data into discrete parts
B. Axial Coding
- Connecting categories and subcategories
- Identifying conditions, strategies, and consequences
- Organizing data into meaningful patterns
C. Selective Coding
- Identifying a core category
- Integrating all categories around the central theme
- Building the final theory
6. Relevance of Grounded Theory in Psychology
Grounded Theory is highly valuable in psychology for several reasons:
1. Builds theory where none exists
Useful in unexplored areas such as:
- cyberbullying experiences
- trauma recovery narratives
- life meaning in chronic illness
2. Captures real-life subjective experiences
Grounded theory provides deep insight into:
- emotions
- coping strategies
- identity formation
- interpersonal relationships
3. Allows flexibility
The study design evolves with data, making it:
- adaptive
- naturalistic
- participant-driven
4. Helps understand psychological processes
GT explains how and why behaviours occur over time.
Example: Process of grief, motivation, addiction recovery.
5. Useful for intervention development
Since theories are grounded in real behaviour, they help design:
- counselling methods
- therapeutic models
- training programs
7. Conclusion
Grounded Theory is a powerful qualitative method that systematically develops theory from data.
Through open, axial, and selective coding, it uncovers deep patterns in human behaviour.
Its emphasis on real-life, lived experience makes it especially important in psychological research where understanding inner processes is essential.
Q12. Differentiate between quantitative and qualitative research.
(6 Marks — very frequently repeated)
Answer
1. Introduction
Psychological research uses two broad approaches: quantitative and qualitative.
Both aim to study human behavior but differ in their purpose, methods, data type, and interpretation.
2. Meaning of Quantitative Research
Quantitative research involves the systematic measurement of variables using numerical data.
It focuses on:
- Testing hypotheses
- Identifying relationships
- Statistical analysis
- Objectivity
Examples:
- Intelligence scores
- Reaction time experiments
- Survey ratings (1–5 scale)
3. Meaning of Qualitative Research
Qualitative research explores human experiences through non-numerical data such as words, narratives, and observations.
It aims to understand:
- Feelings
- Meanings
- Lived experiences
- Social processes
Examples:
- Interview transcripts
- Case histories
- Focus groups
- Observations of behavior
4. Differences Between Quantitative and Qualitative Research
Basis | Quantitative Research | Qualitative Research |
Nature | Objective, numerical | Subjective, descriptive |
Purpose | Test hypotheses, measure variables | Explore meaning, understand experiences |
Data Type | Numbers, scores, statistical data | Words, narratives, interviews |
Methods | Experiments, surveys, standardized tests | Interviews, observations, case studies |
Analysis | Statistical (mean, SD, correlation) | Thematic, content, grounded theory |
Sampling | Large, representative samples | Small, purposive samples |
Outcome | Generalizable findings | In-depth, contextual insights |
Researcher Role | Detached, neutral | Involved, interpretive |
5. When Each Approach Is Useful
Quantitative research is ideal for:
- Measuring psychological constructs
- Comparing groups
- Testing cause–effect relationships
- Large-scale surveys
Qualitative research is ideal for:
- Exploring complex emotions
- Understanding personal experiences
- Studying processes (e.g., coping, grief)
- Developing new theories
6. Conclusion
Both quantitative and qualitative research are essential in psychology.
Quantitative research provides breadth and objectivity, whereas qualitative research provides depth and understanding.
Together, they offer a complete picture of human behaviour and psychological processes.
Q13. Explain the case study method and its applications in psychology.
(10 Marks — Repeated very frequently)
Answer
1. Introduction
The case study method is one of the oldest and most widely used qualitative research methods in psychology.
It involves an in-depth, detailed, and comprehensive analysis of a single individual, group, event, or situation.
Case studies help psychologists understand complex human behavior that cannot be captured through experiments or surveys.
2. Definition of Case Study Method
A case study is an intensive, systematic investigation of a single unit (an individual, family, institution, or community) with the aim of obtaining a complete and holistic understanding of the subject.
Simple definition:
👉 Case study = In-depth study of one case in its real-life context
3. Characteristics of Case Study Method
- Focuses on a single unit
- Provides rich, descriptive data
- Uses multiple sources of information
- Studies the case in its natural setting
- Allows exploration of rare or unique phenomena
- Flexible and open-ended
4. Sources of Data in Case Studies
Case studies usually combine multiple methods:
- Interviews (structured/unstructured)
- Observations
- Psychological tests
- Life histories
- Documents and records
- Diary entries
- Medical or educational reports
Using many sources enhances accuracy (triangulation).
5. Steps in Conducting a Case Study
1. Identification of the Case
Select a case that is unique, significant, or problematic.
2. Collection of Background Information
Gather personal, social, educational, medical, and developmental history.
3. Data Collection Using Multiple Methods
Interviews, tests, observations, and documents.
4. Data Organization
Arrange data into meaningful categories.
5. Data Interpretation
Identify patterns, causes, influences, and psychological processes.
6. Report Writing
Prepare a detailed narrative summarizing findings and conclusions.
6. Types of Case Studies
A. Intrinsic Case Study
Study is conducted because the case itself is unique or interesting.
B. Instrumental Case Study
Case is used to understand a broader psychological issue.
C. Collective (Multiple) Case Study
Several cases are studied together for comparison.
7. Applications of Case Study Method in Psychology
Case studies are widely used in many areas:
1. Clinical Psychology
- Understanding mental disorders
- Diagnosis and treatment planning
- Documenting patient history
- Studying rare psychological conditions
Example: Case of “Little Hans” by Freud.
2. Counseling and Psychotherapy
- Understanding client’s emotional and social problems
- Personal growth, coping strategies, trauma recovery
3. Developmental Psychology
- Studying developmental milestones
- Child growth and behavior patterns
Example: Genie (feral child) case.
4. Abnormal Psychology
- Investigating unusual behaviour
- Dissociative identity disorder, phobias, psychosis
5. Educational Psychology
- Learning disabilities
- Special educational needs
- Behavioural problems in classrooms
6. Neuropsychology
- Study of brain injury and cognitive deficits
Example: Case of Phineas Gage (frontal lobe damage).
7. Organizational Psychology
- Workplace conflicts
- Leadership styles
- Employee motivation
8. Advantages of Case Studies
- Provides deep, detailed insights
- Useful for rare or unique phenomena
- Helps generate new hypotheses
- Offers holistic understanding
- Useful when experiments are not possible
9. Limitations of Case Studies
- Findings may not be generalizable
- Researcher bias may influence interpretation
- Time-consuming
- Lacks control over variables
- Cannot establish cause–effect relationships
10. Conclusion
The case study method is an invaluable tool in psychology, offering rich qualitative data and helping researchers understand complex human experiences.
Although it lacks generalizability, its ability to provide in-depth insights makes it essential in clinical, developmental, abnormal, and neuropsychological research.
Q14. Explain the t-test and its types. Discuss its uses in psychology.
(10 Marks — repeated many times)
Answer
1. Introduction
The t-test is one of the most widely used inferential statistics in psychology.
It helps researchers determine whether the difference between two means is statistically significant or due to chance.
It is especially useful when sample sizes are small (N < 30).
2. Definition of t-test
A t-test is a statistical test used to compare the means of two groups to determine whether the difference between them is significant.
Simple definition:
👉 t-test = A test used to compare two means.
3. Assumptions of t-test
A t-test is valid when:
1. Data are measured on an interval or ratio scale
2. The sample is drawn from a normally distributed population
3. Variances of the groups are equal (homogeneity of variance)
4. Observations are independent
4. Types of t-tests
The t-test has three major types, depending on the research design.
A. Independent Samples t-test (Unpaired t-test)
Used when comparing the means of two separate, independent groups.
Example:
- Comparing anxiety levels of males and females
- Comparing exam scores of control vs experimental groups
Formula (simplified):
t=M1−M2Standard Error of Differencet = \frac{M_1 - M_2}{\text{Standard Error of Difference}}t=Standard Error of DifferenceM1−M2
When used:
- Participants in each group are different
- Between-group designs
B. Paired Samples t-test (Dependent t-test / Matched t-test)
Used when comparing the means of:
- The same group tested twice (pre-test vs post-test)
OR - Matched pairs (e.g., twins, couples)
Examples:
- Stress level before and after meditation training
- Reaction time measured under two different conditions in the same participants
When used:
- Within-subject design
- Repeated measures
C. One-Sample t-test
Used when comparing the mean of one sample with a known population mean.
Example:
Comparing the IQ score of a group of students with the population mean of 100.
When used:
- To check if a sample differs significantly from a standard value
5. Interpretation of t-test
The obtained t-value is compared to a critical t-value from the t-distribution table.
- If t-calculated > t-critical, reject the null hypothesis.
- Means differ significantly.
- If t-calculated < t-critical, fail to reject the null hypothesis.
- Difference is not statistically significant.
6. Uses of t-test in Psychology
The t-test is widely used in psychological research to test hypotheses involving differences between groups or conditions.
1. Comparing Treatment Effects
Used in clinical psychology to compare:
- Effects of counseling
- Drug vs placebo
- CBT vs control group
2. Experimental Psychology
Used to compare:
- Reaction times
- Memory scores under different conditions
- Attention levels before and after training
3. Educational Psychology
Useful for comparing:
- Test scores of boys vs girls
- Achievement before and after a teaching intervention
4. Organizational Psychology
Used to examine:
- Stress levels of employees in two departments
- Job satisfaction before and after a workshop
5. Developmental Psychology
Used to study:
- Cognitive improvement with age
- Effects of parenting styles on behavior
6. Social Psychology
Used to compare:
- Attitude change due to persuasion
- Group differences in conformity or aggression
7. Advantages of t-test
- Easy to compute
- Works well for small samples
- Suitable for interval/ratio data
- Provides information about significance of mean differences
8. Limitations of t-test
- Only compares two groups
- Not suitable for nominal/ordinal data
- Requires normality
- Assumes equal variances
(For more than two groups, ANOVA is used.)
9. Conclusion
The t-test is a foundational statistical tool in psychological research.
It helps determine whether group differences are meaningful or due to chance.
By understanding independent, dependent, and one-sample t-tests, psychologists can design rigorous experiments and draw valid conclusions.
Q15. Explain the Chi-square test and its applications in psychology.
(6 Marks — frequently repeated)
Answer
1. Introduction
The Chi-square (χ²) test is one of the most commonly used non-parametric statistical tests in psychology.
It is used when data are in the form of frequencies (counts) rather than numerical scores.
It helps determine whether the difference between observed and expected frequencies is due to chance.
2. Meaning of Chi-square Test
A Chi-square test examines whether there is a significant association or difference between categorical variables.
Simple definition:
👉 Chi-square = A test used to compare observed frequencies with expected frequencies.
3. Types of Chi-square Tests
A. Chi-square Test of Independence
- Used to find whether two categorical variables are related.
- Example: Gender × Preference for therapy.
B. Chi-square Goodness-of-Fit Test
- Used to check whether a sample fits a theoretical distribution.
- Example: Checking whether responses follow an expected pattern.
4. Formula
χ2=∑(O−E)2E\chi^2 = \sum \frac{(O - E)^2}{E}χ2=∑E(O−E)2
Where:
- O = Observed frequency
- E = Expected frequency
(E is usually calculated using row total × column total / grand total)
5. Assumptions
- Data must be in frequency form, not percentages
- Categories must be mutually exclusive
- Expected frequency in each cell should be at least 5
- Sample observations should be independent
6. Applications of Chi-square Test in Psychology
1. Studying Relationships Between Variables
Used to check association between:
- Gender × Stress coping styles
- Anxiety level × Academic performance categories
- Parenting style × Child behaviour problems
2. Clinical and Counseling Psychology
Used to compare:
- Diagnostic categories
- Types of symptoms
- Treatment preferences of clients
3. Social Psychology
Used to analyze:
- Attitude categories
- Conformity responses (agree/disagree)
- Prejudice categories among groups
4. Educational Psychology
Used to study:
- Grade distribution
- Preferred learning styles
- Pass–fail frequencies across groups
5. Developmental Psychology
Used to compare:
- Developmental milestone categories
- Behavioural categories of children
- Age group vs type of play
6. Survey and Questionnaire Research
Used when responses are categorical:
- Yes/No
- Agree/Disagree
- Category-based responses
7. Conclusion
The Chi-square test is a flexible and powerful non-parametric tool for analysing categorical data in psychology.
It is especially useful when researchers want to determine whether differences in frequencies are meaningful or occurred by chance.
Because of its simplicity and wide applicability, it is one of the most frequently used statistical tests in psychological research.
Q16. Define correlation. Explain its types and applications in psychology.
(10 Marks — repeated many times)
Answer
1. Introduction
In psychology, researchers often study how two variables change together—for example, stress and sleep, intelligence and academic performance, or self-esteem and depression.
Correlation is a key statistical technique used to examine such relationships between variables.
2. Definition of Correlation
Correlation refers to the degree of relationship or association between two variables.
Simple definition:
👉 Correlation = A statistical measure that describes how two variables are related.
Correlation does not imply causation, it only shows how variables move together.
3. Types of Correlation
Correlation can be classified on several bases:
A. Based on Direction of Relationship
1. Positive Correlation
Both variables move in the same direction.
If one increases, the other also increases.
Examples:
- Height and weight
- Study time and academic performance
- Stress and blood pressure
2. Negative Correlation
Variables move in the opposite direction.
If one increases, the other decreases.
Examples:
- Stress and sleep quality
- Self-esteem and depression
- Exercise and body fat
3. Zero (No) Correlation
There is no relationship between the variables.
Example:
- Shoe size and intelligence
- Blood group and personality type
B. Based on Form of Relationship
1. Linear Correlation
Relationship can be described by a straight line.
Example: Hours studied and marks scored.
2. Non-linear (Curvilinear) Correlation
Relationship is curved, not straight.
Example: Stress and performance (Yerkes–Dodson law: moderate stress ↑ performance, high stress ↓ performance)
C. Based on the Statistical Method Used
1. Pearson’s Product Moment Correlation (r)
- Used for interval/ratio data
- Assumes normal distribution
- Most widely used correlation
Range:
−1 to +1-1 \text{ to } +1−1 to +1
2. Spearman’s Rank Order Correlation (ρ or rs)
- Used for ordinal data
- Non-parametric
- Used when data are not normally distributed
Example:
Ranking students by performance and motivation.
3. Point-Biserial Correlation
Used when one variable is continuous and the other is dichotomous (e.g., gender).
4. Phi Coefficient (Φ)
Used when both variables are dichotomous.
4. Interpretation of Correlation Coefficient (r or ρ)
Value | Strength |
0.00 – 0.19 | Very weak |
0.20 – 0.39 | Weak |
0.40 – 0.59 | Moderate |
0.60 – 0.79 | Strong |
0.80 – 1.00 | Very strong |
Sign (+ or –) shows direction.
5. Applications of Correlation in Psychology
Correlation is one of the most widely used tools in psychological research.
1. Studying Relationships Between Psychological Variables
Examples:
- Intelligence and academic achievement
- Anxiety and performance
- Self-esteem and depression
2. Test Construction and Validation
Used to check:
- Reliability of tests (test–retest correlation)
- Validity (correlation between test score and external criterion)
3. Clinical Psychology
Helps identify relationships such as:
- Trauma and PTSD symptoms
- Depression and sleep disturbance
- Substance use and impulsivity
4. Educational Psychology
Used to understand:
- Study habits and exam scores
- Motivation and achievement
- Attendance and performance
5. Personality and Social Psychology
Used to study:
- Aggression and frustration
- Social media use and loneliness
- Attitude and behaviour consistency
6. Developmental Psychology
Correlation helps examine:
- Age and moral reasoning
- Parent–child interaction and emotional development
7. Health and Organizational Psychology
Examples:
- Job satisfaction and productivity
- Stress and absenteeism
- Exercise and mental health
6. Limitations of Correlation
- Does not prove causation
- Influence of third variables
- Only identifies relationships, not explanations
7. Conclusion
Correlation is a fundamental statistical tool in psychology for understanding how variables relate to each other.
By examining positive, negative, or zero relationships, and using Pearson or Spearman methods, psychologists can identify patterns, validate tests, and develop scientific understanding of behaviour.
Q17. Define regression. Explain its types and uses in psychology.
(10 Marks — frequently repeated)
Answer
1. Introduction
Regression is a powerful statistical technique used in psychology to predict the value of one variable based on another.
While correlation tells us the strength of a relationship, regression goes one step further by predicting outcomes.
2. Meaning / Definition of Regression
Regression is a statistical method used to estimate or predict the value of a dependent variable (Y) based on the value of one or more independent variables (X).
Simple definition:
👉 Regression = Prediction of one variable from another.
It helps psychologists understand how much a variable changes when another variable changes.
3. Terms Used in Regression
- Dependent variable (Y): The outcome to be predicted (e.g., exam score).
- Independent variable (X): The predictor (e.g., study hours).
- Regression line: Best-fit line that shows predicted relationship between variables.
- Error term: Difference between predicted and actual values.
4. Regression Equation
For simple linear regression:
Y=a+bXY = a + bXY=a+bX
Where:
- a = intercept
- b = regression coefficient (slope)
- X = predictor
- Y = predicted score
5. Types of Regression
Regression can be classified into two major types depending on the number of independent variables.
A. Simple Regression
In simple regression, one independent variable (X) is used to predict one dependent variable (Y).
Example:
Predicting academic performance (Y) from intelligence score (X).
Interpretation:
The slope (b) tells how much Y changes for every 1-unit change in X.
B. Multiple Regression
Multiple regression uses two or more independent variables to predict one dependent variable.
Example:
Predicting job performance (Y) from:
- motivation (X₁)
- intelligence (X₂)
- personality traits (X₃)
Equation Form:
Y=a+b1X1+b2X2+b3X3+⋯Y = a + b_1X_1 + b_2X_2 + b_3X_3 + \cdotsY=a+b1X1+b2X2+b3X3+⋯
Importance:
Helps understand which variables contribute the most to an outcome.
C. Linear vs. Non-linear Regression
1. Linear Regression
- Relationship between variables is a straight line.
- Most common in psychological research.
Example:
More study hours → higher marks.
2. Non-linear Regression
- Relationship is curvilinear or complex.
- Example: Stress and performance (Yerkes–Dodson Law).
D. Other Types of Regression
(Not always required, but useful for exam depth)
1. Logistic Regression
Used when the dependent variable is categorical (e.g., pass/fail, yes/no).
2. Stepwise Regression
Automatically chooses the best predictors.
3. Hierarchical Regression
Predictors are entered in steps based on theory.
6. Uses / Applications of Regression in Psychology
Regression has wide applications in almost every field of psychology:
1. Predicting Behaviour and Performance
- Predicting academic achievement from intelligence
- Predicting job performance from motivation
- Predicting reaction time from age and fatigue
2. Counseling and Clinical Psychology
Regression helps understand:
- Severity of depression from stress, sleep, and social support
- Predicting relapse in addiction
- Predicting treatment outcomes
3. Test Construction and Validation
- Check how well a test predicts performance
(e.g., aptitude test → job performance)
4. Educational Psychology
- Predicting achievement from study habits and parental involvement
- Predicting dropout risk from attendance and motivation
5. Health Psychology
- Predicting physical health from stress, lifestyle, and coping
- Predicting mental health outcomes from trauma history
6. Social Psychology
Regression is used to understand:
- Aggression from frustration and peer influence
- Prejudice from personality traits and upbringing
7. Developmental Psychology
- Predicting cognitive development from nutrition, SES, and home environment
- Predicting language development from parenting style
7. Advantages of Regression
- Helps in prediction
- Handles multiple predictors
- Identifies the most important variables
- Useful for theory building
8. Limitations of Regression
- Requires large samples
- Assumes linearity
- Sensitive to outliers
- Does not prove causation
9. Conclusion
Regression is an essential statistical tool in psychology.
It helps researchers predict behaviour, identify key influencing variables, and develop scientific models of human functioning.
Through simple and multiple regression, psychologists gain deep insights into the complex relationships among psychological variables.
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ANSWERS 👉 1-5 6-10 11-17 18-27 NUMERICAL QUESTIONS
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