Basic Analysis and Graphing - SAS

100 Performing Bivariate Analysis Chapter 4
Fit Line and Fit Polynomial
Figure 4.9 Example of Equations of Fit
Note: You can edit the equation by clicking on it.
Each Linear and Polynomial Fit Degree report contains at least three reports. A fourth report, Lack of Fit,
appears only if there are X replicates in your data.
Summary of Fit Report
The Summary of Fit reports show the numeric summaries of the response for the linear fit and polynomial
fit of degree 2 for the same data. You can compare multiple Summary of Fit reports to see the improvement
of one model over another, indicated by a larger Rsquare value and smaller Root Mean Square Error.
Figure 4.10 Summary of Fit Reports for Linear and Polynomial Fits
Table 4.4 Description of the Summary of Fit Report
RSquare
Measures the proportion of the variation explained by the model. The
remaining variation is not explained by the model and attributed to random
error. The Rsquare is 1 if the model fits perfectly.
The Rsquare values in Figure 4.10 indicate that the polynomial fit of degree
2 gives a small improvement over the linear fit.
See “Statistical Details for the Summary of Fit Report” on page 125.