Regression 

Regression is a method used to describe the relationship between two variables and to predict one 

variable from another (if you know one variable, then how well can you predict a second variable?).   

Whereas for correlation (see p. 53) the two variables need to have a Normal distribution, in regression 

analysis only the dependent variable Y should have a Normal distribution.  The variable X does not need to 

be a random sample with a Normal distribution (the values for X can be chosen by the experimenter).  

However, the variability of Y should be the same for each value of X. 

When you select Regression in the menu, the following box appears on the screen: 

In this dialog box you identity 2 variables.  If you want to select the variables from the variables list, click 

the 

  button and now you can select the variable in the list.  Next, you move the cursor to the 

Independent X field, and again you click the 

 button to select the variable in the list. 

Optionally, you may also enter selection criteria in order to include only a selected subgroup of cases in the 

statistical analysis.  Again, you can click the 

 button to obtain a list of selection criteria already used for 

the current data. 

Finally, a regression equation (regression model, equation of approximating curve) has to be selected.  

The program offers a choice of 5 different equations: 

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