Which statistical test is best suited for determining differences between more than two groups?

The one-way ANOVA is the appropriate statistical test for determining differences between more than two groups because it allows for the comparison of the means of multiple independent groups simultaneously. This test is designed specifically to assess whether there is a statistically significant difference among the group means. By evaluating the variance within and between the groups, one-way ANOVA can effectively highlight differences that may exist due to various factors affecting the populations being studied.

In contrast, a paired t-test is utilized specifically for comparing two related groups, such as measurements taken from the same subjects before and after an intervention. The chi-square test assesses the association between categorical variables rather than the means of groups and is not appropriate for comparing more than two means. Regression analysis examines the relationship between variables and is not aimed at comparing multiple group means either, making one-way ANOVA the clear choice for this specific scenario.