Conducting stepwise regression
- Select Stat >> Regression >> Stepwise...
- In the box labeled Response, specify the response.
- In the box labeled Predictors, specify all the
predictors that you want considered for the model (including the ones
that appear in the following Predictors to include in every
- (Optional) In the box labeled Predictors to include in every
model, specify all of the predictors that must be included
in every model considered.
- (Optional) Under Methods..., specify the Alpha
to enter and Alpha to remove significance
levels. The default for both is 0.15. Select OK.
- Select OK. The output will appear in the session window.
Researchers were interested in learning how the composition of cement
affected the heat evolved during the hardening of the cement. Therefore,
they measured and recorded the following data (cement.txt)
on 13 batches of cement:
- Response y: heat evolved in calories during hardening of
cement on a per gram basis
- Predictor x1: % of tricalcium aluminate
- Predictor x2: % of tricalcium silicate
- Predictor x3: % of tetracalcium alumino ferrite
- Predictor x4: % of dicalcium silicate
Perform stepwise regression on the data set. Let αE
= αR = 0.15. In doing so, require that the
predictor x2 be included in all models considered.
Close this window when finished.
© 2004 The Pennsylvania State University. All rights reserved.
Materials developed by Dr. Laura J. Simon (Lecturer, Penn State Department of Statistics).