Fundamentals of Statistics contains material of various lectures and courses of H. Lohninger on statistics, data analysis and chemometrics......click here for more. 
See also: regression, ANOVA  
ANOVA and Regression
A powerful procedure to obtain more information on the quality of a
regression model is the analysis of variances (ANOVA). The idea behind
ANOVA is to split the variances within a model into several parts, which
then can be set in relationship to each other, thus uncovering facts about
the model. ANOVA can thus be used to check the validity a model, and the
goodness (or, lack) of fit. Basically we have to distinguish between two
cases:
The general scheme of the breakdown of errors is as follows
In the case of measurements without replicates the ANOVA has to be carried out according to the following scheme. If the resulting F value exceeds the critical value F_{α;(1,n2)}, the null hypothesis H_{0} that the slope b of the line is equal to zero has to be rejected.


Last Update: 20121008