Should Pearson's correlation coefficient be avoided?

Investigators should be alert to whether: (1) the relationship between two variables could be non-linear, (2) the data are bivariate normal, (3) r accounts for a significant proportion of the variance in Y, (4) outliers are present, the data are clustered, or have a restricted range, (5) the sample size is appropriate, and (6) a significant correlation indicates causality. In addition, the number of significant digits used to express r and the problems of multiple testing should be addressed. The problems and limitations of r suggest a more cautious approach regarding its use and the application of alternative methods where appropriate.