Statistics for Behavioural Science – Inferentials

Important Questions for MSU B.Sc. Psychology 4th Sem (April 2026)

Subject: Statistics for Behavioural Science – Inferentials
Course: B.Sc. Psychology 4th Semester
University: Manonmaniam Sundaranar University (MSU)

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📘 Introduction

Statistics plays an important role in behavioural science research and psychological testing. Inferential statistics helps psychologists draw conclusions about populations based on sample data. This unit includes important concepts such as correlation, regression, Z-test, t-test, ANOVA, and non-parametric tests.

This post contains important 1-mark, 5-mark, and 8-mark university examination questions prepared according to the latest MSU B.Sc. Psychology syllabus for April 2026 examinations.

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🔵 1 MARK QUESTIONS (MCQ)

Unit I: Correlation & Regression

1. A scattergram is used to show the relationship between ___ variables.
2. The value of Pearson's r ranges between:
   a) 0 to 1 b) -1 to 0 c) -1 to +1 d) 0 to ∞
3. Partial correlation controls for the effect of:
   a) One variable b) Two variables c) A third variable d) None
4. The Coefficient of Determination is denoted by:
   a) r b) r² c) R d) b
5. Standard Error of Estimate is used in:
   a) Correlation b) Regression c) ANOVA d) Z-test
6. Multiple correlation measures the relationship between ___ independent variables and one dependent variable.

Unit II: Large & Small Sample Tests

7. Z-test is used when sample size is:
   a) n < 30 b) n > 30 c) n = 10 d) n = 5
8. t-test for two dependent samples is also called:
   a) Paired t-test b) Independent t-test c) Z-test d) F-test
9. Degrees of freedom for one-sample t-test =
   a) n b) n-1 c) n-2 d) n+1
10. The critical value for Z at 5% level of significance (two-tailed) is:
    a) 1.96 b) 2.58 c) 1.645 d) 3.00

Unit III: ANOVA

11. ANOVA was developed by:
    a) Pearson b) Spearman c) R.A. Fisher d) Student
12. In One-way ANOVA, the variance is partitioned into ___ components.
13. Two-way ANOVA considers ___ independent variables.
    a) One b) Two c) Three d) Four
14. The test statistic used in ANOVA is:
    a) t b) Z c) F d) χ²

Unit IV: Non-Parametric Tests

15. Chi-square test was developed by:
    a) Fisher b) Karl Pearson c) Spearman d) Mann
16. Mann-Whitney U test is the non-parametric alternative to:
    a) One-sample t-test b) Independent t-test c) Paired t-test d) ANOVA
17. The Run Test is used to test:
    a) Correlation b) Randomness c) Variance d) Mean difference
18. Kruskal-Wallis test is a non-parametric alternative to:
    a) t-test b) One-way ANOVA c) Two-way ANOVA d) Z-test

Unit V: Non-Parametric Correlations

19. Spearman's Rank Order correlation uses:
    a) Raw scores b) Ranks c) Percentages d) Frequencies
20. Phi coefficient is used when both variables are:
    a) Continuous b) Ordinal c) Dichotomous d) Nominal

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🟡 5 MARK QUESTIONS

Unit I

1. Explain the properties and limitations of the Product Moment Correlation Coefficient.
2. What is Partial Correlation? State its assumptions and limitations.
3. Write a note on Coefficient of Determination with an example.
4. Explain the concept of Standard Error of Estimate in regression.
5. What are the assumptions of regression analysis?

Unit II

1. Distinguish between Z-test and t-test with suitable examples.
2. Explain t-test for two independent samples with its assumptions.
3. Write a note on the critical values of Z-statistics and their significance.
4. When is t-test for dependent samples used? Give an example from psychology.

Unit III

1. What is One-way ANOVA? Explain its procedure and assumptions.
2. State the advantages of Two-way ANOVA over One-way ANOVA.
3. Explain the concept of variance partitioning in ANOVA.

Unit IV

1. What are non-parametric tests? State their advantages and disadvantages.
2. Explain the Chi-square test with its characteristics and limitations.
3. Write a short note on the Sign Test and Median Test.
4. Explain the Friedman Test with its assumptions.

Unit V

1. Explain Point Bi-serial correlation with its assumptions and limitations.
2. What is Tetrachoric Correlation? When is it used?
3. Write a note on Phi Coefficient with numerical example.

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🔴 8 MARK QUESTIONS

Unit I

1. Explain Pearson's Product Moment Correlation Coefficient – concept, formula, properties, assumptions, and numerical computation.
2. Write an essay on Multiple Correlation – Coefficient of Determination, properties, and limitations.
3. Explain Simple and Multiple Regression – applications, assumptions, numerical computation, and limitations.
4. Compare Partial Correlation and Multiple Correlation with examples and numerical illustrations.

Unit II

1. Explain Z-test in detail – critical values, Z-test for one sample, Z-test for two independent samples, and test of significance with examples.
2. Write an essay on t-tests – t-test for one sample, two independent samples, and two dependent samples with numerical examples.
3. Differentiate between large sample and small sample tests with applications in behavioural science research.

Unit III

1. Explain One-way ANOVA in detail – model, procedure, assumptions, and numerical computation.
2. Explain Two-way ANOVA – advantages, important terminologies, model, procedure, assumptions, and numerical computation.
3. Compare One-way and Two-way ANOVA with suitable psychological research examples.

Unit IV

1. Write an essay on Non-Parametric Tests – meaning, advantages, disadvantages, Chi-square test, Run Test, Sign Test, Median Test with numerical examples.
2. Explain Mann-Whitney U Test and Kruskal-Wallis Test with their assumptions, numerical computation, and limitations.
3. Explain the Friedman Test in detail with assumptions, procedure, and numerical computation.

Unit V

1. Write an essay on Non-Parametric Correlations – Rank Order, Bi-serial, Point Bi-serial, Tetrachoric, and Phi Coefficient with their assumptions and limitations.
2. Compare parametric and non-parametric correlations with suitable examples from behavioural science.
3. Explain Bi-serial and Point Bi-serial Correlation – differences, assumptions, numerical computation, and limitations.

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📚 How to Prepare for Statistics Exams

• Focus on formulas and statistical procedures.
• Practice numerical problems regularly.
• Learn assumptions and limitations of each statistical test.
• Study differences between parametric and non-parametric tests.
• Revise critical values such as Z = 1.96 and important t-table values.
• Write answers using proper statistical terminology.

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💡 Exam Tip: For 8-mark answers, always include — Definition → Formula/Procedure → Assumptions → Example/Numerical → Limitations. For MCQs, focus on critical values (Z = 1.96, t-table), test conditions (n > 30 for Z), and who developed each test.

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📌 Related Topics

• Research Methods in Psychology
• Experimental Psychology
• Psychological Testing and Assessment
• Descriptive Statistics
• Behavioural Science Research Methods

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📢 Disclaimer

This material is prepared only for educational and revision purposes for students of MSU B.Sc. Psychology. Questions are collected and organized based on syllabus-oriented important topics and previous examination patterns. MH Educational Blog does not guarantee that the same questions will appear in the university examination. Students are advised to refer to their prescribed textbooks, class notes, and university syllabus for complete preparation.