Talk:Hotelling's T-squared distribution

Hi Michael

that was a good edit!

I suppose if the observations are rank deficient, that would be equivalent to them all lying in a (p − 1)-dimensional hyperplane. I can't quite visualize the effect on $W^{-1}$. Any ideas as to how to "see" what's going on in this case?

best

Robinh 22:07, 26 Feb 2005 (UTC)

I'll think about that one. But notice that if the sample size is smaller than p, then you would necessarily have a rank deficiency. Michael Hardy 23:13, 26 Feb 2005 (UTC)

Confusing

Hello,

Could someone add a brief, common-sense explanation of what the T-square statistic actually is for? I have a somewhat vague idea, but nothing certain. Such an addition would be a much appreciated preface to the mathematical details. Thanks, 65.183.135.231 (talk) 04:58, 26 August 2008 (UTC)

Hi. The T-square statistic is a generalization of Student's t statistic that is used in multivariate hypothesis testing (cut-and-pasted from the article). In what way does this fall short of what you ask for? Best wishes, Robinh (talk) 07:10, 26 August 2008 (UTC)

Relation to Mahalanobis distance

The only difference is the factor of N. I have been trying to compare the results from some statistical software but I do not quite see their results to show this relationship. Shyamal (talk) 07:12, 26 December 2008 (UTC)

Results

Hello, How do you view your data set? as a set of n vectors of p samples each, or p samples of a single vector of n dimensions? So long as you are consistent, the results are consistent withe 'cov()' function in 'R'. I've checked my own function against the returns of cov(). —Preceding unsigned comment added by 129.198.241.62 (talk) 19:33, 22 June 2010 (UTC)