Correlation Analysis

Correlation analysis is used to predict the value of a variable based upon information on an independent variable.

Correlation analysis is the first step in creating a parametric model. Parametric analysis assumes that your data is Gaussian. You can help make your data Gaussian by eliminating outliers using data filtering (see Filtering Data) and/or performing data transformation (see Transforming Data). After correlation analysis, you perform factor analysis and generate equations. Then you choose Parametric Analysis to build your model.

To perform a correlation analysis of the data:

1	Choose Analysis > Correlation Analysis.

2	The data is analyzed, reorganized, and presented in the Correlation Matrix folder.

Click the Parameters tab if you wish to view the data as it was presented before the correlation analysis.