Anova Regression And Residual. Many scientists thing of residual as values that are obtained with regression. The residual is the bit thats left when you subtract the predicted value from the observed value.
ANOVA for Regression Analysis of Variance ANOVA consists of calculations that provide information about levels of variability within a regression model and form a basis for tests of significance. Recall when considering significance for simple regression the t-test for the significance of the pairwise correlation between x and y the t-test for the significance of the slope of y sim x and the ANOVA F-test for the proportion of variance in y accounted for by x all gave us the same result. Because the data set includes replications anova partitions the residual SumSq into the part for the replications Pure error and the rest Lack of fit.
ANOVA residuals dont have to be anywhere close to normal in order to fit the model.
But ANOVA is really regression in disguise. Many scientists thing of residual as values that are obtained with regression. In ANOVA the variance due to all other factors is subtracted from the residual variance so it is equivalent to full partial correlation analysis. In the case of regression the number of the error term is one.
