# Model Building Summary (linear models)

When a model selection algorithm other than None is chosen on the Model Selection settings, this provides some details of the model building process.

**Forward stepwise. **When forward stepwise is the selection
algorithm, the table displays the last 10 steps in the stepwise algorithm.
For each step, the value of the selection criterion and the effects
in the model at that step are shown. This gives you a sense of how
much each step contributes to the model. Each column allows you to
sort the rows so that you can more easily see which effects are in
the model at a given step.

**Best subsets. **When best subsets is the selection algorithm,
the table displays the top 10 models. For each model, the value of
the selection criterion and the effects in the model are shown. This
gives you a sense of the stability of the top models; if they tend
to have many similar effects with a few differences, then you can
be fairly confident in the "top" model; if they tend to have very
different effects, then some of the effects may be too similar and
should be combined (or one removed). Each column allows you to sort
the rows so that you can more easily see which effects are in the
model at a given step.