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Mann Whitney U aka Wilcoxon Rank-Sum Test in R (R Tutorial 4.3) Video Lecture | Mastering R Programming: For Data Science and Analytics - Database Management
FAQs on Mann Whitney U aka Wilcoxon Rank-Sum Test in R (R Tutorial 4.3) Video Lecture - Mastering R Programming: For Data Science and Analytics - Database Management
| 1. What is the Mann-Whitney U test and how is it related to the Wilcoxon Rank-Sum test? |  |
Ans. The Mann-Whitney U test, also known as the Wilcoxon Rank-Sum test, is a nonparametric statistical test used to compare two independent groups. It is used to determine whether there is a significant difference between the medians of the two groups. The test is based on ranking the observations from both groups and comparing the sums of ranks between the groups.
| 2. When should I use the Mann-Whitney U test instead of a t-test? | |
Ans. The Mann-Whitney U test should be used when the assumptions of the t-test are not met. It is a nonparametric test, meaning it does not rely on assumptions about the distribution of the data. Therefore, it is more appropriate when the data is skewed or when outliers are present. Additionally, the Mann-Whitney U test can be used when the data is ordinal or when the sample sizes are small.
| 3. How do I interpret the results of the Mann-Whitney U test? | |
Ans. The results of the Mann-Whitney U test provide a U statistic and a p-value. The U statistic represents the sum of the ranks for one of the groups. A lower U value indicates that the group with the lower ranks has a significantly higher distribution. The p-value represents the probability of observing the data given that the null hypothesis is true. If the p-value is less than the chosen significance level (usually 0.05), we reject the null hypothesis and conclude that there is a significant difference between the groups.
| 4. Can I use the Mann-Whitney U test for more than two groups? | |
Ans. No, the Mann-Whitney U test can only be used to compare two independent groups. If you have more than two groups, you would need to use a different test, such as the Kruskal-Wallis test, which is an extension of the Mann-Whitney U test for multiple independent groups.
| 5. Is the Mann-Whitney U test robust to outliers? | |
Ans. Yes, the Mann-Whitney U test is robust to outliers. Since the test is based on the ranks of the data rather than the actual values, extreme values have less impact on the results. However, it is important to note that if the outliers are influential and not representative of the population, it may still be appropriate to remove or address them before conducting the test.
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