UGC NET Exam > UGC NET Videos > Psychology for UGC NET > Quick Revision: T test, Z test, F test, Chi-square test, ANOVA, Mann-Whitney U Test, H test
Quick Revision: T test, Z test, F test, Chi-square test, ANOVA, Mann-Whitney U Test, H test Video Lecture | Psychology for UGC NET
FAQs on Quick Revision: T test, Z test, F test, Chi-square test, ANOVA, Mann-Whitney U Test, H test Video Lecture - Psychology for UGC NET
| 1. What is the difference between T-test and Z-test? |  |
Ans. The T-test is used when the sample size is small (typically less than 30) and the population standard deviation is unknown, while the Z-test is applicable for larger sample sizes (30 or more) or when the population standard deviation is known. The T-test accounts for more variability due to smaller sample sizes, making it more suitable for estimating population parameters when limited data is available.
| 2. When should I use ANOVA instead of a T-test? | |
Ans. ANOVA (Analysis of Variance) is used when comparing the means of three or more groups, whereas a T-test is limited to comparing the means of two groups. If you have multiple groups and wish to determine if at least one group mean is different from the others, ANOVA is the appropriate choice.
| 3. What are the assumptions of the Chi-square test? | |
Ans. The assumptions of the Chi-square test include: (1) the data must be categorical, (2) the observations should be independent of each other, (3) the expected frequency in each category should be at least 5, and (4) the sample size should be sufficiently large to ensure the validity of the test results.
| 4. How do I interpret the results of the Mann-Whitney U Test? | |
Ans. The Mann-Whitney U Test is a non-parametric test used to compare the differences between two independent groups. A U value is calculated, and this value is then compared to a critical value from the Mann-Whitney distribution. If the calculated U value is less than or equal to the critical value, the null hypothesis is rejected, indicating a significant difference between the two groups.
| 5. What is the purpose of the F-test in statistics? | |
Ans. The F-test is used to compare the variances between two or more groups to determine if they are significantly different from each other. It is commonly used in the context of ANOVA to test the hypothesis that the means of different populations are equal by examining the ratio of the variances between the groups.
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