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- Path: sparky!uunet!gatech!purdue!mentor.cc.purdue.edu!pop.stat.purdue.edu!hrubin
- From: hrubin@pop.stat.purdue.edu (Herman Rubin)
- Newsgroups: sci.math.stat
- Subject: Re: Testing for Normality
- Message-ID: <Bu5suB.HxM@mentor.cc.purdue.edu>
- Date: 6 Sep 92 13:44:34 GMT
- References: <1992Sep5.064647.15570@constellation.ecn.uoknor.edu>
- Sender: news@mentor.cc.purdue.edu (USENET News)
- Organization: Purdue University Statistics Department
- Lines: 27
-
- In article <1992Sep5.064647.15570@constellation.ecn.uoknor.edu> bateman@nsslsun.nssl.uoknor.edu (Monte Bateman) writes:
- >I would like to test data for normality. The books I have
- >access to talk about graphing frequencies on "probability paper".
-
- >First off, I don't have any.
-
- >Second, it seems that there should be software available
- >to do this test.
-
- >Pointers?
-
- >Any/all help appreciated!
-
-
- There is no shortage of tests for normality. One problem is that the
- behavior of the test statistic, even the size, is generally not computable
- except by simulation, even approximately. The problem is also to get a
- reasonably good test against the most likely alternatives.
-
- The Kolmogorov-Smirnov test with the parameters, assuming normality,
- estimated from the data is not difficult to calculate. There are tables
- of the significance levels.
- --
- Herman Rubin, Dept. of Statistics, Purdue Univ., West Lafayette IN47907-1399
- Phone: (317)494-6054
- hrubin@pop.stat.purdue.edu (Internet, bitnet)
- {purdue,pur-ee}!pop.stat!hrubin(UUCP)
-