2) Create a Correlation Matrix using Spearman and Pearson.

This Blog entry is from the Linear Regression section in Learn Palisade.

Correlation is a measure of relationship and direction of that relationship.  It is a single value that ranges from -1 to +1, which would signal the direction and strength of a relationship.  Both -1 and +1 in their extremes are equally interesting.  A correlation matrix takes all the variables together and produces the correlation value between each variable.  This matrix will be the bedrock, starting point, for many of the techniques used in the following Blog entries.

In the StatTools ribbon, towards the centre of the ribbon select summary statistics then the sub menu Correlation and Covariance:


The correlation and covariance window will open:


In this Blog entry perform correlation analysis against all abstracted variables, this is the Independent and Dependent variables created.  Start by selecting all variables.  Towards the top left of the variables grid right click, then click select all:


Upon having selected all the variables, deselect the raw variables in the file – this is all variables before the dependent variable in this example:


Notice that the Correlation analysis is set to Pearson Linear, while the Covariances is also selected.  Covariances are superfluous to this Blog entry and can be deselected:


Click OK to produce the Correlation matrix.  NOTE THAT THIS MAY TAKE SOME TIME IN EXTREMLY LARGE DATASETS.  The correlation matrix will return after some time processing: