ASCA,<unk> -SCA, or analysis of variance –<unk><unk>  analysis is a method that partitions variation and enables interpretation of these partitions by SCA, a method that is similar to PCA. This method is an multi or even megavariate extension of<unk> . The variation partitioning is similar to Analysis of variance<unk> . Each partition matches all variation induced by an effect or factor, usually a treatment regime or experimental condition. The calculated effect partitions are called effect estimates. Because even the effect estimates are multivariate, interpretation of these effects estimates is not intuitive. By applying SCA on the effect estimates one gets a simple interpretable result. In case of more than one effect this method estimates the effects in such a way that the different effects are not correlated.
ANOVA-simultaneous component analysis
Shapiro-Wilk test
Bartlett's test
Analysis of rhythmic variance
Linear regression
Kendall tau rank correlation coefficient
Non-parametric statistics
Brown-Forsythe test