Before deciding which correlation test to run, which two assumptions need to be checked?
A) Linearity
B) Normality
C) Effect size
D) z-score

Question

Quizplus · Accepted Answer

When deciding which correlation test to use, it is important to check for linearity and normality. Linearity refers to the relationship between the two variables being measured. If the relationship is nonlinear, a different type of correlation test such as Spearman's rank correlation may be more appropriate. Normality refers to the distribution of data points for each variable being measured. If the data is not normally distributed, this can impact the validity of the correlation test results. Therefore, checking for linearity and normality is important when deciding which correlation test to run. Other factors like effect size and z-score are not relevant when deciding on the appropriate correlation test.

Before Deciding Which Correlation Test to Run, Which Two Assumptions