Comments on: Why heights are not normally distributed http://www.johndcook.com/blog/2008/07/20/why-heights-are-not-normally-distributed/ The blog of John D. Cook Sat, 11 Feb 2012 22:42:11 -0500 http://wordpress.org/?v=2.8.4 hourly 1 By: Ellie K http://www.johndcook.com/blog/2008/07/20/why-heights-are-not-normally-distributed/comment-page-1/#comment-45655 Ellie K Fri, 03 Sep 2010 20:56:20 +0000 http://www.johndcook.com/blog/2008/07/20/why-heights-are-not-normally-distributed/#comment-45655 I'd agree that the normal distribution is a fine thing for most in the middle. Yet effectively capturing frequency distributions using probability models, particularly when you have mostly normal data, but some extremely extreme outliers can be done. That's what kurtosis and skew are for! With physical systems, things DO tend to break down at extreme points. Even though that isn't your point here, it elicited thoughts of fault tolerances and boundary values, when processes and machines reach their tolerance points and cease functioning. I realize that that is a different matter than the traditional mean = 0, stdev = 1, skew = 0 and kurtosis = 4 (I think!) normal distribution breaking down at extreme upper and lower intervals of the data distribution? Is there an anaolgy there? Not even that? More? Please explain if you have time. I know some things, but you know more. Thank you. PS I am enjoying your blog immensely! I’d agree that the normal distribution is a fine thing for most in the middle. Yet effectively capturing frequency distributions using probability models, particularly when you have mostly normal data, but some extremely extreme outliers can be done. That’s what kurtosis and skew are for!

With physical systems, things DO tend to break down at extreme points. Even though that isn’t your point here, it elicited thoughts of fault tolerances and boundary values, when processes and machines reach their tolerance points and cease functioning.

I realize that that is a different matter than the traditional mean = 0, stdev = 1, skew = 0 and kurtosis = 4 (I think!) normal distribution breaking down at extreme upper and lower intervals of the data distribution? Is there an anaolgy there? Not even that? More? Please explain if you have time. I know some things, but you know more. Thank you.
PS I am enjoying your blog immensely!

]]> By: nanotürkiye http://www.johndcook.com/blog/2008/07/20/why-heights-are-not-normally-distributed/comment-page-1/#comment-25360 nanotürkiye Thu, 01 Oct 2009 08:14:36 +0000 http://www.johndcook.com/blog/2008/07/20/why-heights-are-not-normally-distributed/#comment-25360 Did you e-mailed the author of the book, to include these 2 posts (Why are heights normal and not normal)? :) Thank you for this brief and informative post. Did you e-mailed the author of the book, to include these 2 posts (Why are heights normal and not normal)? :)

Thank you for this brief and informative post.

]]> By: Sean http://www.johndcook.com/blog/2008/07/20/why-heights-are-not-normally-distributed/comment-page-1/#comment-22139 Sean Thu, 06 Aug 2009 03:46:11 +0000 http://www.johndcook.com/blog/2008/07/20/why-heights-are-not-normally-distributed/#comment-22139 Hi! You should write books! Ah... It was refreshing that you can actually explain statistical data (and some of its weakness) it such a clear and concise manner... Thanks! Sean. P.S. People actually read this! And like it! Hi!
You should write books! Ah… It was refreshing that you can actually explain statistical data (and some of its weakness) it such a clear and concise manner…
Thanks!
Sean.

P.S. People actually read this! And like it!

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