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Chapter 10
Multiple Regression
Fitting Plane
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It’s easy to visualize two regressors predicting a response by using fitting planes. But how can this be
done with more regressors when the analysis requires more than three dimensions? In actuality, the
fitting, testing, and leverage plot analyses still work for more regressors.
Select Analyze > Fit Model. Fill the window with Oxy as Y and add Age, Weight, Runtime,
RunPulse, and MaxPulse as model effects.
Click Run Model to run the model.
In this case, the prediction formula is
Oxy = 101.3 - 0.2123 Age - 0.0732 Weight - 2.688 Runtime - 0.3703
RunPulse + 0.3055 MaxPulse
Look at the significance of each regressor with t-ratios in the Parameter Estimates table or F-ratios in
the Effects Tests table. (See Figure 10.9.) Because each effect has only one parameter, the F-ratios are
the squares of the t-ratios, and have the same significance probabilities.
The Age variable seems significant, but Weight does not. The Runtime variable seems highly
significant. Both RunPulse and MaxPulse also seem significant, but MaxPulse is less significant than
RunPulse.
Figure 10.9 Statistical Tables for Multiple Regression
10 Multiple Regression
More and More Regressors