Correlation can be defined as the linear relationship between multiple variables. Positive, negative, and no correlation are the three scenarios that can exist. The values range from -1 to 1. A positive correlation is observed when the value of one variable increases with the increase of another variable, whereas in negative correlation, with an increase in the value of one variable, the value of another variable decreases.
Correlation is often run as a precursor to evaluating the role of variables in models such as regression. In the following instance, we have multiple variables in the Var statement that are being assessed as predictors for the Stock variable. The Date variable is an ID variable and is not being assessed:
Proc Corr Data = Model;
ID Date;
With Stock;
Var Basket_Index -- M1_Money_Supply_Index;
Run;
The Corr procedure produces basic statistical measures similar...