Which test is used to determine if the mean scores of two groups are significantly different?

The T-Test is used to determine if the mean scores of two groups are significantly different. This statistical test assesses whether the averages of two independent samples are different from each other. It is particularly useful when the sample data are normally distributed and when the variances of the two groups can be assumed to be equal (in its standard form known as the independent samples t-test).

The t-test calculates the t-statistic, which measures the size of the difference relative to the variation in the sample data. If the t-statistic is greater than the critical value from the t-distribution (based on the degrees of freedom and desired significance level), it indicates that there is a statistically significant difference between the means of the two groups.

Other tests listed serve different purposes: the Chi-Square Test is primarily used for categorical data to assess how the observed frequencies compare to the expected frequencies; ANOVA (Analysis of Variance) is applied when comparing means across three or more groups; and the Mann-Whitney U Test is a non-parametric alternative to the t-test that assesses whether the ranks of two independent samples differ. Therefore, the t-test is the appropriate choice for assessing mean differences between two groups specifically.