When dealing with continuous data from related or paired samples, which statistical test is appropriate?

The paired t-test is the appropriate statistical test for analyzing continuous data from related or paired samples because it specifically examines the means of two related groups. This scenario often arises in studies where measurements are taken from the same subjects under two different conditions or at two different times, such as before and after a treatment.

In a paired t-test, the differences between the paired observations are calculated, and these differences are then analyzed to determine whether the mean difference is statistically significantly different from zero. This test is grounded in the assumption that the differences are normally distributed, which is why it’s suitable for data that meets this requirement.

Choosing a test designed for independent samples, like the Student t-test, would ignore the paired relationship of the data. The Mann Whitney U test, on the other hand, is a non-parametric alternative for independent samples and would not be appropriate for paired data. Similarly, a one-way ANOVA is used for comparing means across more than two groups and does not apply to the direct comparison of two related groups. Thus, a paired t-test is the ideal choice for the scenario presented.