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Mann Whitney U aka Wilcoxon Rank-Sum Test in R (R Tutorial 4.3)

In this video you will learn to conduct the Wilcoxon Rank-Sum (aka Mann-Whitney U) test in R, which is the non-parametric alternative to the independent t-test.

First, we will explain when it is appropriate to use the Mann-Whitney U aka Wilcoxon Rank-Sum test to analyze data. Then we will show you how to use the "wilcox.test" command in R to conduct this nonparametric test of examining the difference in median for two independent populations. Here you will first learn to visually examine the relationship between two independent variables using boxplot before conducting Mann-Whitney U or Wilcoxon Rank-Sum test.

Next, we will demonstrate how to conduct the two-sided nonparametric test using the "wilcox.test" command and how to let R know that the difference in medians for the independent populations is 0 by using the "mu" argument. In this tutorial you will learn to ask R to calculate a two-sided alternative using the "alt" argument, to let R return a nonparametric confidence interval using the "conf.int" argument, and to set the level of confidence interval using the "conf.level" argument.

Moreover, you will learn to specify that the groups be not paired using the "paired" argument, to ask R to return an exact p-value using the "exact" argument, and to ask R to use a continuity correction using the "correct" argument.

We recommend using the link below to download the dataset and practice on your own while watching this tutorial.

 

You can access and download the dataset that was used in this tutorial here:

Tab Delimited LungCapDataset for R TutorialsExcel LungCap Dataset for R Tutorials

 

 

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