The Mahalanobis distance takes into account the correlation structure of the data and the individual scales. For each value, the Mahalanobis distance is denoted Mi and is computed as

Y is the row of means

n = number of observations

p = number of variables (columns)

n = number of observations

p = number of variables (columns)

T2 Distance Measures

n = number of observations

p = number of variables (columns)