Which statistical test would you use to compare the means of two independent groups?

The independent t-test is the appropriate statistical test to use when comparing the means of two independent groups. This test assesses whether there is a statistically significant difference between the average values of the two groups under consideration.

In this context, "independent groups" refers to two distinct sets of observations that do not influence each other. For instance, one group might consist of patients receiving a certain treatment, while the other group might consist of patients receiving a placebo. The independent t-test assumes that the data is normally distributed and that the variances of the two groups are equal (or at least similar), although there are variations like Welch’s t-test that can be used for cases where this assumption does not hold.

The paired t-test, on the other hand, is designed for scenarios where the measurements in the two groups are related or matched, such as pre-treatment and post-treatment measurements of the same subjects. The chi-square test is used for categorical data to determine if there is a significant association between two variables, making it unsuitable for comparing means. ANOVA (Analysis of Variance) is used when comparing the means of three or more groups, thus not applicable when only two groups are being compared.

Thus, with the aim of comparing the means of