Which test is used to examine the relationship between two continuous variables?

• A. ANOVA
• B. Chi-square cross tabulation
• C. T-test
• D. Pearson's correlation coefficient

Answer: (D)

When you want to know how two continuous variables relate to each other, you look at their association, and Pearson's correlation coefficient is the standard measure for a linear relationship. It tells you both the strength and the direction of how the variables move together: a value close to 1 means a strong positive linear relationship, close to -1 means a strong negative linear relationship, and around 0 suggests little linear association. It also provides a p-value to assess whether the observed relationship could occur by chance.

This is the best choice here because the question asks about the relationship between two continuous variables. The other tests are for different scenarios: ANOVA compares means across groups defined by a categorical variable, Chi-square cross tabulation looks at association between two categorical variables, and a t-test compares means between two groups for one continuous outcome. If the relationship isn’t linear or the data are not suitable for Pearson (for example, they’re ordinal or heavily non-normal), a different measure like Spearman’s rho might be more appropriate, but Pearson’s is the go-to for two continuous, linearly related variables.