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*[[Multivariate normal distribution|Multivariate normality]]: Independent variables are normal for each level of the grouping variable.<ref name="green"/><ref name="buy"/>
*Homogeneity of variance/covariance ([[homoscedasticity]]): Variances among group variables are the same across levels of predictors. Can be tested with [[Box'
▲*Homogeneity of variance/covariance ([[homoscedasticity]]): Variances among group variables are the same across levels of predictors. Can be tested with [[Box's_M_test|Box's M]] statistic.<ref name="green"/>{{page needed|date=April 2012}} It has been suggested, however, that [[linear discriminant analysis]] be used when covariances are equal, and that [[quadratic classifier#Quadratic discriminant analysis|quadratic discriminant analysis]] may be used when covariances are not equal.<ref name="buy"/>
*[[Multicollinearity]]: Predictive power can decrease with an increased correlation between predictor variables.<ref name="buy"/>
*[[statistical independence|Independence]]: Participants are assumed to be randomly sampled, and a participant’s score on one variable is assumed to be independent of scores on that variable for all other participants.<ref name="green"/><ref name="buy"/>
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