A new technique for assessing multivariate normality (MVN) is proposed in this work based on a beta transform of the multivariate normal data set. The statistic is the sum of interpoint squared distances between an ordered set of the transformed observations and the set of the beta population pth quantiles. We showed that the statistic is affine invariant. The critical values of the test were evaluated for different sample sizes and different random vector dimensions through extensive simulations. For some selected sample sizes and random vector dimensions, the empirical type-I-error rates and powers of the proposed test were compared with those of others already in use tests for MVN. The results showed that the test is a good and competitive tool for testing MVN.
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