The Summary of Fit report shows a summary for a one-way analysis of variance.
Rsquare
Measures the proportion of the variation accounted for by fitting means to each factor level. The remaining variation is attributed to random error. The R2 value is 1 if fitting the group means account for all the variation with no error. An R2 of 0 indicates that the fit serves no better as a prediction model than the overall response mean. See the statistical details for the Summary of Fit Report.
R2 is also called the coefficient of determination.
Note: A low RSquare value suggests that there might be variables not in the model that account for the unexplained variation. However, if your data are subject to a large amount of inherent variation, even a useful ANOVA model can have a low RSquare value. Read the literature in your research area to learn about typical RSquare values.
Adj Rsquare
Adjusts R2 to make it more comparable over models with different numbers of parameters by using the degrees of freedom in its computation. See the statistical details for the Summary of Fit Report.
Root Mean Square Error
Estimates the standard deviation of the random error. It is the square root of the mean square for Error found in the Analysis of Variance report.
Mean of Response
The overall mean (arithmetic average) of the response variable.
Observations (or Sum Wgts)
Number of observations used in estimating the fit. If weights are used, this is the sum of the weights. See the statistical details for the Summary of Fit Report.