If I were to use Spearman's rho as a measure of correlation, must the data I'm working with be normally distributed/homoscedastic?
Also, if I am plotting the data against time, must the data be time-independent?
Solved – Assumptions for Spearman’s rho test for correlation
assumptionsspearman-rho
Best Answer
Spearman's rho is nonparametric. There are no distributional assumptions. Interpreting the Pearson correlation as strength of linearity and tests for statistical significance rely on bivariate normality for Pearson. Homoskedasticity never enters in for any correlation. Remember it only has to do with the bivariate pair (X,Y) that you are calculating correlations for. Regression doesn't enter in unless in the case of Pearson you want to the slope of the regression of X on Y. When you say you are plotting with time is time a variable included in the correlation? If you are just looking at pairs that are from a time dependent sequence, there is no need to make any assumptions about time. If you are correlating X with time T then Spearman's rho is used to see if there is a relationship between X and T and then clearly you don't want to assume T is independent of X.