T-test Statistics in R: Independent Samples, Paired Sample, and One Sample T-tests

This chapterT-test providesPaired sample the readersOne sample with the steps and guidelines on how to run the T-testT-test in R. This test is used for evaluating the meansMeans of one or two groups of variables in research experiments or statistical tests. By definition, the t-test is one of the inferential (parametric) statistics that are used for hypothesis testing, and for determining the differences (where applicable) between the meansMeans of two independent groups of data or single variable in a data sample. The most common types of the test namely—Independent samples, Paired samplePaired sample, and One sampleOne sample t-tests are explained and practically illustrated in this chapter. The Independent samples t-test (also referred to as Unpaired or Two-sample t-test) is used by the researchers to compare the meansMeans for two independently sampled groups, where the two groups under consideration are independent of each other. On the other hand, Paired sample t-test (also known as Dependent sample t-test) is applied to compare the meansMeans of a sample collected from the same group or population but at different time or interval (e.g., pre and post test, before and after). While the One sample t-test is used when the researcher wants to compare the mean of a single group of variables or data alongside a known mean, i.e., test whether the given sample mean is equal to the hypothesized data value otherwiseStandard deviation known as the test mean.