Which of the following tests are associated with the association/validity category?

Which of the following tests are associated with the association/validity category?

• A. Pearson and Spearman correlation
• B. T-test
• C. ANOVA
• D. Kaplan-Meier

Answer: (A)

Assessing whether two variables are related is about measuring association. Pearson and Spearman correlation are built for that purpose. They quantify how one variable tends to move with another. Pearson looks at linear relationships between continuous variables and gives a coefficient that reflects both strength and direction of that linear link. Spearman, on the other hand, ranks the data and detects monotonic relationships, which makes it useful when the data aren’t normally distributed or when you’re working with ordinal ranks. Both are about co-variation between measures, which is why they fit the association/validity category. The other tests focus on comparing group means or on time-to-event outcomes rather than on the relationship between two variables. A t-test examines whether the average of one group differs from another. ANOVA extends that idea to more groups. Kaplan-Meier analyzes survival probabilities over time. These aren’t about how two variables relate to each other, so they belong to different areas.

Assessing whether two variables are related is about measuring association. Pearson and Spearman correlation are built for that purpose. They quantify how one variable tends to move with another. Pearson looks at linear relationships between continuous variables and gives a coefficient that reflects both strength and direction of that linear link. Spearman, on the other hand, ranks the data and detects monotonic relationships, which makes it useful when the data aren’t normally distributed or when you’re working with ordinal ranks. Both are about co-variation between measures, which is why they fit the association/validity category.

The other tests focus on comparing group means or on time-to-event outcomes rather than on the relationship between two variables. A t-test examines whether the average of one group differs from another. ANOVA extends that idea to more groups. Kaplan-Meier analyzes survival probabilities over time. These aren’t about how two variables relate to each other, so they belong to different areas.