In which scenario is an independent samples t-test appropriate?

• A. Independent samples t-test for two different groups.
• B. Paired t-test for related observations (repeated measures).
• C. ANOVA when comparing more than two groups.
• D. Chi-square test for categorical data.

Answer: (A)

The main idea here is using an independent samples t-test when you want to compare the average score on a continuous outcome between two separate groups. The key requirement is that observations in one group are independent of observations in the other group, and you’re looking at means, not counts or categories. This makes the test appropriate for two different groups (for example, a treatment group and a control group with different participants). The classic version assumes the data are approximately normally distributed in each group and, ideally, have similar variances (though there’s a Welch version if variances differ). The other scenarios don’t fit: a paired t-test is for related observations like the same people measured twice; ANOVA is for comparing means across three or more groups; and a chi-square test is for relationships between categorical variables, not means of a continuous measure.