Multivariate analysis of variance: Difference between revisions

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First, define the following <math display="inline">n\times q</math> matrices:
 
* <math display="inline">Y</math>: where the <math display="inline">i</math>-th row is equal to <math display="inline">y_i</math><br />
 
* <math display="inline">\hat Y</math>: where the <math display="inline">i</math>-th row is the best prediction given the group membership <math display="inline">g(i)</math>. That is the mean over all observation in group <math display="inline">g(i)</math>: <math display="inline">\frac{1}{\text{size of group }g(i)}\sum_{k: g(k)=g(i)}y_k</math>.<br />
 
* <math display="inline">\bar Y</math>: where the <math display="inline">i</math>-th row is the best prediction given no information. That is the [[Sample mean and covariance|empirical mean]] over all <math display="inline">n</math> observations <math display="inline">\frac{1}{n}\sum_{k=1}^n y_k</math>