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Re: Stats: Testing whether data is normally (Gaussian) distributed

by moklevat (Priest)
on Apr 27, 2007 at 21:25 UTC ( [id://612458]=note: print w/replies, xml ) Need Help??


in reply to Stats: Testing whether data is normally (Gaussian) distributed

Hi andye,

It looks like it may be a trade-off between calling R or coding the algorithm yourself, and a smashing opportunity to write a module:-). Among the options for tests of normality you might consider Shapiro-Wilk, (there is a link to a Fortran version of the algorithm in the Wikipedia article), and the popular Kolmogorov-Smirnov test. The K-S is generalizable to many distributions, but may be more of a pain to implement than Shapiro-Wilk. I would recommend steering clear of the Anderson-Darling test, as it is overly sensitive with sample sizes greater than about 25 (as mentioned in Wikipedia).

If you do roll your own, PDL is great for stats.

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