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Wilcoxon Signed Rank Test in R (R Tutorial 4.5)

In this video, you will learn to conduct the Wilcoxon Signed Rank test in R. This test is the non-parametric alternative to the paired t-test (R Tutorial 4.4). The Wilcoxon Signed Rank test is used for paired or matched groups/observations: e.g., observation #1 in group 1 is dependent on observation #1 in group 2. This should not be confused with the Wilcoxon Rank Sum aka Mann-Whitney U test (R Tutorial 4.3), which is for independent groups. These two tests use the same command in R, except that we use the "paired" argument to change between the two, by setting it to TRUE or FALSE.

In this tutorial we will first explain when it is appropriate to use the Wilcoxon Signed Rank Test to analyze the data. We will start by examining the data visually by producing a boxplot. Then we will show you how to perform Wilcoxon Signed Rank Test using the "wilcox.test" command.

In this video, you will learn to use additional arguments on the "wilcox.test" command to make it more fitting for your analysis. For example, you will learn to test the hypothesis of whether the difference in medians is 0 using the "mu" argument, have a two-sided test or two-sided alternative using the "alt" argument, let R know that the two populations are paired or dependent using "paired" argument, ask R to return a confidence interval using "conf.int" argument and specify the confidence level using "conf.level" argument. Moreover, You will be able to ask R to calculate an approximate p-value and an approximate confidence interval using "exact" argument, and to not use a continuity correction for the Wilcoxon Signed Rank Test 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 BloodPressure Dataset for R TutorialsExcel BloodPressure Dataset for R Tutorials

 

 

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