ABSTRACT
This chapter examines the darker recesses of common statistical measures that are Linear and Rank Correlation. Of those in use, estimators would probably find that Pearson's Linear Correlation is used the most frequently because it is relatively simple to calculate with tools such as Microsoft Excel. Pearson's Linear Correlation Coefficient for two variables is a measure of the extent to which a change in the value of one variable can be associated with a change in the value of the other variable through a linear relationship. As such it is a measure of linear dependence or linearity between the two variables, and can be calculated by dividing the Covariance of the two variables by the Standard Deviation of each variable. The Coefficient of Determination is a statistical index which measures how much of the total variance in one variable can be explained by the variance in the other variable.
