APPLIED MULTIVARIATE STATISTICS: WITH SAS® SOFTWARE

1.6. Tests for Multivariate Normality

Often before doing any statistical modeling, it is crucial to verify if the data at hand satisfy the underlying distributional assumptions. Many times such an examination may be needed for the residuals after fitting various models. For most multivariate analyses, it is thus very important that the data indeed follow the multivariate normal, or if not exactly at least approximately. If the answer to such a query is affirmative, it can often reduce the task of searching for procedures which are robust to the departures from multivariate normality. There are many possibilities for departure from multivariate normality and no single procedure is likely to be robust with respect to all such departures from the ...