Hi all, I have a dataset of 2000 numbers ( it's noise measured with a scoop ) Now i want to know of my data is normal distributed (Gaussian distribution). I did already: - 68-95-99.7 test - Q-Q-plot and now i used "nortest library" and the Lilli.test() However i don't understad the output? lillie.test(z) Lilliefors (Kolmogorov-Smirnov) normality test data: z D = 0.0218, p-value = 0.0278 I read wiki, but still can understand it.. Can anyone, give an explanation of my output D and p-value? Thanks in advance Gr. Bosken -- View this message in context: http://n4.nabble.com/Normal-distribution-Lillie-test-tp1565083p1565083.html Sent from the R help mailing list archive at Nabble.com.
Hi, As far as I understand, D is the value of (Kolmogorov-Smirnov) statistic and p-value is the probability to get that (or greater) value for normally distributed variables (so in your case you would most probably reject the hypothesis that your data is normal). --- On Tue, 23/2/10, Bosken <jens.bossaert at kahosl.be> wrote:> From: Bosken <jens.bossaert at kahosl.be> > Subject: [R] Normal distribution (Lillie.test()) > To: r-help at r-project.org > Received: Tuesday, 23 February, 2010, 7:22 AM > > Hi all, > > I have a dataset of 2000 numbers ( it's noise measured with > a scoop ) > > Now i want to know of my data is normal distributed > (Gaussian distribution). > > I did already: > > - 68-95-99.7 test > - Q-Q-plot > > and now i used "nortest library" and the Lilli.test() > > However i don't understad the output? > > lillie.test(z) > > ??? Lilliefors (Kolmogorov-Smirnov) > normality test > > data:? z > D = 0.0218, p-value = 0.0278 > > I read wiki, but still can understand it.. > > Can anyone, give an explanation of my output D and > p-value? > > Thanks in advance > > Gr. Bosken > > > > -- > View this message in context: http://n4.nabble.com/Normal-distribution-Lillie-test-tp1565083p1565083.html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > R-help at r-project.org > mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, > reproducible code. >
Hi, Thanks for your reaction; How do you come to the decision that my data not is normal distributed? With the 69-95-99.7 test and Q-Q plot seems it ok! But these test are not exact, they only give you an image. Gr. Bosken -- View this message in context: http://n4.nabble.com/Normal-distribution-Lillie-test-tp1565083p1565762.html Sent from the R help mailing list archive at Nabble.com.
You should probably read fortune(117) and fortune(234) (and possibly some of the original discussions that lead to the fortunes). Reading the help page for the SnowsPenultimateNormalityTest function (TeachingDemos package) may also help. If you are happy with the plots, but still feel the need for a "test" of some sort, then you should investigate using the vis.test function in the TeachingDemos package. Hope this helps, -- Gregory (Greg) L. Snow Ph.D. Statistical Data Center Intermountain Healthcare greg.snow at imail.org 801.408.8111> -----Original Message----- > From: r-help-bounces at r-project.org [mailto:r-help-bounces at r- > project.org] On Behalf Of Bosken > Sent: Tuesday, February 23, 2010 4:13 AM > To: r-help at r-project.org > Subject: Re: [R] Normal distribution (Lillie.test()) > > > Hi, > > Thanks for your reaction; > > How do you come to the decision that my data not is normal distributed? > > With the 69-95-99.7 test and Q-Q plot seems it ok! But these test are > not > exact, they only give you an image. > > Gr. Bosken > -- > View this message in context: http://n4.nabble.com/Normal-distribution- > Lillie-test-tp1565083p1565762.html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting- > guide.html > and provide commented, minimal, self-contained, reproducible code.
... But,quoting Pogo, "We have met the enemy, and he is us." Normality tests are standard fare in a host of statistical texts. Bert Gunter Genentech Nonclinical Biostatistics -----Original Message----- From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf Of Greg Snow Sent: Thursday, February 25, 2010 9:00 AM To: Bosken; r-help at r-project.org Subject: Re: [R] Normal distribution (Lillie.test()) You should probably read fortune(117) and fortune(234) (and possibly some of the original discussions that lead to the fortunes). Reading the help page for the SnowsPenultimateNormalityTest function (TeachingDemos package) may also help. If you are happy with the plots, but still feel the need for a "test" of some sort, then you should investigate using the vis.test function in the TeachingDemos package. Hope this helps, -- Gregory (Greg) L. Snow Ph.D. Statistical Data Center Intermountain Healthcare greg.snow at imail.org 801.408.8111> -----Original Message----- > From: r-help-bounces at r-project.org [mailto:r-help-bounces at r- > project.org] On Behalf Of Bosken > Sent: Tuesday, February 23, 2010 4:13 AM > To: r-help at r-project.org > Subject: Re: [R] Normal distribution (Lillie.test()) > > > Hi, > > Thanks for your reaction; > > How do you come to the decision that my data not is normal distributed? > > With the 69-95-99.7 test and Q-Q plot seems it ok! But these test are > not > exact, they only give you an image. > > Gr. Bosken > -- > View this message in context: http://n4.nabble.com/Normal-distribution- > Lillie-test-tp1565083p1565762.html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting- > guide.html > and provide commented, minimal, self-contained, reproducible code.______________________________________________ R-help at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.