Which of the following tests would you choose if you have normally distributed data and want to compare two groups?

The T-test for independent means is the appropriate choice when you have normally distributed data and wish to compare the means of two independent groups. This test assumes that the data follows a normal distribution, which allows for the application of statistical techniques that evaluate the differences in the means while controlling for variation within the samples. The T-test assesses whether the observed differences between the groups are statistically significant, helping to determine if any observed effects are likely due to chance or if they represent true group differences.

In contrast, the Wilcoxon signed-rank test is designed for comparing two related groups and is used with ordinal data or when normality cannot be assumed. The Mann-Whitney U test also compares two independent groups but is more suitable for non-normally distributed data or when the data is ordinal. The Chi-square test evaluates the relationship between categorical variables rather than comparing means, making it unsuitable for this context. Therefore, the T-test for independent means is specifically suited for this scenario due to its reliance on the assumption of normality and is therefore the correct choice.