The pages I quoted were associated with the second edition but I believe the pictures are the same in both editions, but the page numbers may differ.

Also, what you are saying seems reasonable, irenab (thank you).

Still, I think the illustration was meant to compare a normal distribution, which is the dotted line and reflects "no excess kurtosis," and a distribution with high kurtosis, which I interpret to mean positive excess kurtosis. The solid line is labelled as high kurtosis but does not reflect this fact simply because the curve is LESS peaked than the no excess kurtosis curve.

Yet, you bring up an interesting question. I know that the t-distribution is leptokurtotic, which means that the distribution has excess kurtosis. Also, the t-distribution approaches the normal distribution as n approaches infinity, so I deduce that as n approaches infinity, the excess kurtosis for the t-distribution approaches 0. I also deduce from this that the t-distribution will be leptokurtotic for all n less than infinity, so it should alwaysbe more peaked and fatter tails than the normal distribution. Now here is the rub; I have always been told that the t-distribution is similar to the normal distribution but is flattened somewhat, as if pressure was applied to the peak and probability was spread to the tails. (Most pictures of the t indicate the same.)

But if this is the case, then it is contradictory to say that the t-distribution is leptokurtotic.....essentially, it comes down to this: My understanding of leptokurtosis is that the peak of the distribution is HIGHER and SKINNIER and the tails are FATTER versus the normal distribution. Based on the t-distributions I have seen, it appears impossible to have a Higher peak, and therefore, impossible to have excess kurtosis.....

Anyone care to opine

Thanks!

Brian

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