Monday, April 27, 2015

t-test (parametric) in SPSS and R & Wilcoxon Signed-Rank (nonparametric) test

Example: Suppose we would like to know does the use of a mobile phone while driving change reaction time. We have 6 individuals and tested their reaction time with and without mobile as below:


1. In the SPSS, choose [Analyze]->[Compare Means]->[Paired-Samples T Test]


2. Add variables

3. Click OK and the SPSS will do all the jobs for you..

4. two-tailed to one-tailed
 If you wanted the one-tailed significance value, just divide the two-tailed value in half.


Robust t-test in R


The Wilcoxon Signed-Rank (nonparametric) test

 Parametric tests such as t-test are based on assumptions about the distribution of the underlying population from which the sample was taken. The most common parametric assumption is that data are approximately normally distributed.

The Wilcoxon Signed-Rank (nonparametric) test is a non-parametric counterpart to the paired-samples t-test, which can be used in the case of the data is not normally distributed. The pros and cons can be found at https://www.mayo.edu/mayo-edu-docs/center-for-translational-science-activities-documents/berd-5-6.pdf
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