Anova Assumptions Residuals. Residuals as before to classify outliers Leverage values. The four assumptions are.
If there is a non-random pattern the nature of the. Create histogram of response values. The longer useful answer is this.
In this article Im going to focus on the assumptions that the error terms or residuals have a mean of zero and constant variance.
The assumptions are exactly the same for ANOVA and regression models. ANOVA assumes that residuals errors are normally distributed and terms have equal variance homoscedasticity antonym heteroscedasticity. If the assumptions are met the residuals will be randomly scattered around the center line of zero with no obvious pattern. The difference between the observed value of the dependent variable y and the predicted value ŷ is called the residual e.
