Editing Linear discriminant analysis (section)

==Eigenvalues==
An [[eigenvalues and eigenvectors|eigenvalue]] in discriminant analysis is the characteristic root of each function.{{clarify|date=April 2012}} It is an indication of how well that function differentiates the groups, where the larger the eigenvalue, the better the function differentiates.<ref name="buy"/> This however, should be interpreted with caution, as eigenvalues have no upper limit.<ref name="green"/><ref name="buy"/>
	The eigenvalue can be viewed as a ratio of ''SS''<sub>between</sub> and ''SS''<sub>within</sub> as in ANOVA when the dependent variable is the discriminant function, and the groups are the levels of the [[Instrumental variable|IV]]{{clarify|date=April 2012}}.<ref name="green"/> This means that the largest eigenvalue is associated with the first function, the second largest with the second, etc..