**Multivariate Normality Test**

*Multivariate normal distribution **or multivariate
Gaussian distribution* is a
generalization of the one-dimensional (univariate

If *X* and *Y* are normally distributed and **independent**, this implies they are
"jointly normally distributed", i.e., the pair (*X*, *Y*)
must have bivariate normal distribution. However, *a pair of jointly normally distributed
variables need not be independent*.

*The fact that a set of random variables
X _{1}, X_{2}, …, X_{i},
each has a normal distribution does not imply that the they have a joint
normal distribution. *

This function performs
the Shapiro-Wilk test for multivariate normality.

Below is a **sample input window**:

Below is a **sample output**:

Multivariate normality test for:

Y0

Y1

Y2

Y3

Y4

Y5

Shapiro-Wilk normality test

data:
Z

W = 0.5889, p-value < 2.2e-16