Which statistical test is used when a single measure is taken from two groups of subjects?

The appropriate statistical test for analyzing a single measure taken from two different groups of subjects is the independent (unpaired) t test. This test is utilized when the goal is to determine if there is a statistically significant difference between the means of two independent groups.

In this scenario, each group's data is collected separately and independently from the other group. The independent t test evaluates whether the average values for the two groups differ significantly, taking into account the variation within each group. It is essential for the groups to be independent, meaning that the subjects in one group should not influence or be related to the subjects in the other group.

In contrast, a dependent (paired) t test is used when the measurements are not independent, typically when the same subjects are measured twice, such as before and after a treatment. ANOVA is appropriate for comparing means across three or more groups rather than just two. A correlation test assesses the relationship between two continuous variables rather than comparing group means.

Thus, the independent (unpaired) t test is the correct choice, as it is specifically designed for situations where you have two separate groups and want to compare their means based on a single measure.