What statistical method is used to compare mean scores at different times in the same group?

The paired samples t-test is the appropriate statistical method for comparing mean scores at different times within the same group. This procedure is particularly useful in longitudinal studies or repeated measures designs, where the same subjects are evaluated at two or more different time points.

The essence of the paired samples t-test lies in its ability to account for the fact that the measurements made at various times are related. Since the same participants provide data across different occasions, the test looks at the differences between pairs of observations rather than treating them as independent. It calculates whether the average of these differences is significantly different from zero, indicating changes over time.

This method is especially powerful because it mitigates variability due to individual differences, as it focuses on changes within the same subjects rather than between different subjects. This focus increases the sensitivity of the test when detecting real changes in the data.

In contrast, other statistical methods mentioned would not be suitable for this context. For instance, the independent samples t-test compares means between two separate groups and is not appropriate when the same subjects are involved. ANOVA is typically used to compare means among three or more groups, not necessarily over time. The chi-square test is designed for categorical data to assess relationships or differences in frequencies, rather than for means in continuous