📚 Topic Summary
Analysis of Variance (ANOVA) is a powerful tool, but it relies on certain assumptions about your data, such as normality and equal variances. When these assumptions are violated, non-parametric alternatives offer robust solutions. These alternatives, like the Kruskal-Wallis test or the Friedman test, don't require the same strict assumptions and can be used with ordinal or non-normally distributed data. Knowing when to switch is key to accurate statistical analysis! Understanding when to use these alternative tests is crucial for making accurate inferences from your data, especially in fields like medicine, social sciences, and engineering.
🔤 Part A: Vocabulary
Match the following terms with their definitions:
| Term |
Definition |
| 1. ANOVA |
a. A non-parametric test used to compare three or more related groups. |
| 2. Non-parametric Test |
b. A statistical test that does not require specific assumptions about the distribution of the data. |
| 3. Kruskal-Wallis Test |
c. A statistical test used to compare the means of three or more independent groups. |
| 4. Mann-Whitney U Test |
d. A non-parametric test used to compare two independent groups. |
| 5. Friedman Test |
e. A parametric test used to compare the means of three or more independent groups. |
(Answers: 1-e, 2-b, 3-c, 4-d, 5-a)
✍️ Part B: Fill in the Blanks
Complete the following paragraph with the correct words:
When the assumptions of _________ are violated, consider using a __________ test. For example, if your data is not normally distributed or has unequal _________, the __________ test can be used to compare multiple independent groups. If you have repeated measures and the data is non-parametric, the __________ test would be more appropriate than repeated measures ANOVA.
(Answers: ANOVA, non-parametric, variances, Kruskal-Wallis, Friedman)
🤔 Part C: Critical Thinking
Describe a real-world scenario where you would choose the Kruskal-Wallis test over a one-way ANOVA. Explain why the Kruskal-Wallis test is more appropriate in that situation.