Correlation is useful for trying to identify the different strengths of association that may exist between two or more variables. After running correlation, you will get a correlation matrix with values between -1 and 1. Each individual value indicates the strength and direction of the associated variables. In the output, there will always be a series of values that equal 1 because it is a variable being compared with itself. Short variable names are recommended for a matrix that is easier to read.
- Drag over all the variables of interest into the Selected Variable(s) box (A)
- If desired, select which correlation methodology you would like to use (B)
- Click Run (C)
Available Correlation Methodologies
- Pearson - linear relationships/continuous variables
- Kendall - ordinal association between measure quantities
- Spearman - ranked values, non-parametric