Analysis of Variance for Linear Models
The Analysis of Variance table for linear models,
shown in Figure 39.11, includes the following:
- indicates the source of the variation.
Sources include Model for the fitted
regression and Error for the residual error.
C Total is the sum of the Model and Error components,
and it is the total variation after correcting for the mean.
When the model does not have an intercept term, the
uncorrected total variation (U Total) is displayed.
- is the degrees of freedom associated
with each source of variation.
- Sum of Squares
- is the sum of squares for each source of variation.
- Mean Square
- is the sum of squares divided by its
associated degrees of freedom.
- F Stat
- is the F statistic for testing the null hypothesis
that all parameters are 0 except for the intercept.
This is formed by dividing the mean square
for model by the mean square for error.
- Pr > F
- is the probability of obtaining a greater F statistic
than that observed if the null hypothesis is true.
This quantity is also called a p-value.
A small p-value is evidence
for rejecting the null hypothesis.
Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.