STATISTICS IN PSYCHOLOGY (MPC-006)
TUTOR MARKED ASSIGNMENT
SECTION – A
Answer the following question in about 1000 words (wherever applicable) each.
1. Discuss hypothesis testing with a focus on general procedure for testing a hypothesis and error in hypothesis testing.
2. Using ANOVA find out if significant difference exists between the scores obtained by the three groups of students on self concept.
|
Group A |
34 | 23 | 32 | 34 | 54 | 34 | 22 | 35 | 38 | 43 |
|
Group B |
12 | 14 | 45 | 18 | 23 | 24 | 26 | 27 | 32 |
29 |
| Group C | 23 | 32 | 34 | 45 | 23 | 22 | 21 | 26 | 32 |
33 |
3. Discuss the concept of normal curve. Explain the characteristics of normal probability curve with the help of suitable diagrams.
SECTION – B
Answer the following questions in about 400 words (wherever applicable) each.
4. Discuss assumption, advantages and disadvantages of nonparametric statistics.
5. Compute Pearson’s Product Moment Correlation for the following two sets of scores.
|
Data 1 |
7 | 8 | 6 | 5 | 3 | 5 | 9 | 16 | 12 | 12 |
| Data 2 | 2 | 4 | 10 | 6 | 13 | 10 | 1 | 5 | 3 |
4 |
6. With the help of Mann Whitney ‘U’ test find if significant difference exists between the scores obtained on organizational climate scale by male and female employees in an organization.
|
|
Scores on Organizational Climate Scale |
| Male Employees | 23, 34, 45, 54, 56, 45, 45, 54, 56, 67, 32, 31, 23, 25, 29, 30 |
| Female Employees |
56, 43, 34, 45, 56, 54, 32, 33, 31, 34, 32, 35, 56, 65, 43, 67 |
7. Describe two way ANOVA and discuss its merits and demerits.
8. Compute Chi-square for the following data:
|
Phases of Adolescents |
Achievements Motivation Scores | ||
|
|
High | Average |
Low |
|
Early |
23 | 25 |
23 |
|
Middle |
33 | 34 |
12 |
| Late | 54 | 45 |
23 |
SECTION – C
Answer the following in about 50 words each
9. The median test
10. Ogive
11. Level of significance
12. Positive and negative relationship
13. Phi coefficient
14. Multiple regression
15. Outliers
16. Measuring Kurtosis
17. Wilcoxon matched pair rank test
18. Sampling error and standard error