Question 1

Explain the fundamental concepts in determining the significance of the difference between Means.

Accepted Answer

Determining the significance of the difference between means is a fundamental process in psychological research, allowing us to ascertain if an observed difference between two groups or conditions is likely a true effect or merely due to random chance. As per BPCC-108, this involves a systematic application of hypothesis testing principles.

Firstly, the process begins with formulating the Null Hypothesis (H₀) and the Alternative Hypothesis (H₁). The null hypothesis typically states that there

Question 2

Compute One Way ANOVA (parametric statistics) for the following data: Scores obtained on Emotional Intelligence Scale. Group A: 3, 3, 2, 2, 4, 3, 2, 1, 2, 4. Group B: 4, 1, 1, 2, 3, 4, 2, 2, 3, 4. Group C: 3, 4, 5, 3, 2, 4, 4, 2, 2, 2.

Accepted Answer

One-Way Analysis of Variance (ANOVA) is a parametric statistical test used to determine if there are any statistically significant differences between the means of three or more independent (unrelated) groups. As outlined in BPCC-108, it partitions the total variability in the data into components attributable to differences between groups and variability within groups, allowing us to test the null hypothesis that all group means are equal.

For the given data on Emotional Intelligence Scale sc

Question 3

Explain the concept of non parametric statistics and describe its assumptions.

Accepted Answer

Non-parametric statistics are a group of statistical methods that do not rely on assumptions about the specific distribution (e.g., normal distribution) of the population from which the data is drawn. They are often called "distribution-free" tests and are preferred when parametric assumptions cannot be met or with certain types of data.

The primary assumption of non-parametric statistics is the absence of assumptions regarding the underlying population distribution, such as normality. However

Question 4

Compute Chi square for the following data: Junior Managers: Males 3, Females 8. Senior Managers: Males 7, Females 3.

Accepted Answer

The Chi-square (χ²) test examines the association between two categorical variables, such as management level and gender. For the given data (Junior Managers: Males 3, Females 8; Senior Managers: Males 7, Females 3), we first calculate observed and expected frequencies using the formula χ² = Σ [(O - E)² / E].

The observed frequencies are presented in the contingency table:
| Category      | Males (O) | Females (O) | Row Total |
|---------------|-----------|-------------|-----------|
| Junior Mg

Question 5

Compute Mann Whitney U for the following data: Group A Scores: 3, 4, 12, 14, 31, 7, 26, 19, 21, 16. Group B Scores: 10, 5, 15, 13, 9, 30, 33, 24, 18, 20.

Accepted Answer

As per BPCC-108, to compute Mann Whitney U, combine Group A (n₁=10) and Group B (n₂=10) scores and rank them lowest to highest.

After ranking all 20 scores, the sum of ranks for Group A (R₁) is found to be 98. For Group B, the sum of ranks (R₂) is 112.

Next, calculate U₁ using the formula: U₁ = n₁n₂ + [n₁(n₁+1)]/2 - R₁. Substituting values: U₁ = (10)(10) + [10(11)]/2 - 98 = 100 + 55 - 98 = 57.

Similarly, calculate U₂: U₂ = n₁n₂ + [n₂(n₂+1)]/2 - R₂. Substituting values: U₂ = (10)(10) + [10(11)

Question 6

Describe the various types of factorial designs with the help of suitable example.

Accepted Answer

Factorial designs examine the effects of two or more independent variables (factors) on a dependent variable simultaneously, allowing for the analysis of both main effects and interaction effects.

One type is the **Between-Subjects Factorial Design**, where different groups of participants are assigned to each unique combination of factor levels. For instance, in a 2x2 design studying 'Intervention Type' (Cognitive Restructuring vs. Relaxation Training) and 'Anxiety Severity' (High vs. Low) on

Question 7

Compute Kruskal Wallis ANOVA test for the following data: Group A Scores: 4, 5, 7, 9, 12. Group B Scores: 5, 3, 2, 7, 4.

Accepted Answer

The Kruskal-Wallis H-test, a non-parametric test from BPCC-108, compares medians of two or more independent groups when assumptions for one-way ANOVA are violated.

First, combine all 10 scores (N=10) and rank them from 1 (lowest) to 10 (highest). Tied scores are assigned the average rank.
Group A Scores & Ranks: (4, 3.5), (5, 5.5), (7, 7.5), (9, 9), (12, 10).
Group B Scores & Ranks: (2, 1), (3, 2), (4, 3.5), (5, 5.5), (7, 7.5).

Next, calculate the sum of ranks (R) for each group:
R_A = 3.5 + 5

Question 8

Explain the procedure for computation of Independent t test using SPSS.

Accepted Answer

The computation of an Independent t-test in SPSS begins by navigating the menu system. First, click on 'Analyze', then hover over 'Compare Means', and finally select 'Independent-Samples T Test'. This opens a dialog box where you will specify your variables for analysis.

Next, transfer your continuous dependent variable (the outcome you're measuring, e.g., 'Anxiety_Score') into the 'Test Variable(s)' box. Subsequently, move your categorical independent variable (the grouping variable with exact

BPCC-108 Solved Assignment — January 2026 / July 2025

STATISTICAL METHODS FOR PSYCHOLOGICAL RESEARCH- II | IGNOU Bachelor of Arts (Sociology) (BAFSO)

BPCC-108—January 2026 / July 2025

STATISTICAL METHODS FOR PSYCHOLOGICAL RESEARCH- II

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BPCC-108 Assignment Questions — January 2026

Q1. Explain the fundamental concepts in determining the significance of the difference between Means.

Q2. Compute One Way ANOVA (parametric statistics) for the following data: Scores obtained on Emotional Intelligence Scale. Group A: 3, 3, 2, 2, 4, 3, 2, 1, 2, 4. Group B: 4, 1, 1, 2, 3, 4, 2, 2, 3, 4. Group C: 3, 4, 5, 3, 2, 4, 4, 2, 2, 2.

Q3. Explain the concept of non parametric statistics and describe its assumptions.

Q4. Compute Chi square for the following data: Junior Managers: Males 3, Females 8. Senior Managers: Males 7, Females 3.

Q5. Compute Mann Whitney U for the following data: Group A Scores: 3, 4, 12, 14, 31, 7, 26, 19, 21, 16. Group B Scores: 10, 5, 15, 13, 9, 30, 33, 24, 18, 20.

Q6. Describe the various types of factorial designs with the help of suitable example.

Q7. Compute Kruskal Wallis ANOVA test for the following data: Group A Scores: 4, 5, 7, 9, 12. Group B Scores: 5, 3, 2, 7, 4.

Q8. Explain the procedure for computation of Independent t test using SPSS.

QActivity 3. Take any one block from BPCC108 and write a review of the same in about 1000 words. The review needs to be in your own words and should cover the important aspects of the block.

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