hotelling_t2test2
              Compute Hotelling’s T^2 ("T-squared") test for two independent samples.
 For two samples x from multivariate normal distributions with
 the same number of variables (columns), unknown means and unknown
 equal covariance matrices, test the null hypothesis
 mean (x) == mean (y).
 hotelling_t2test2 treats NaNs as missing values, and ignores the
 corresponding rows for each sample independently.
 Name-Value pair arguments can be used to set statistical significance.
 "alpha" can be used to specify the significance level of the test
 (the default value is 0.05).
If h is 1 the null hypothesis is rejected, meaning that the tested samples do not come from the same multivariate distribution. If h is 0, then the null hypothesis cannot be rejected and it can be assumed that both samples come from the same multivariate distribution.
The p-value of the test is returned in pval.
stats is a structure containing the value of the Hotelling’s test statistic in the field "Tsq", and the degrees of freedom of the F distribution in the fields "df1" and "df2". Under the null hypothesis, $$ {(n_x+n_y-p-1) T^2 \over p(n_x+n_y-2)} $$ has an F distribution with and degrees of freedom, where and are the sample sizes and is the number of variables.
See also: hotelling_t2test
Source Code: hotelling_t2test2