> -----Original Message----- > From: [EMAIL PROTECTED] [mailto:r-help- > [EMAIL PROTECTED] On Behalf Of [EMAIL PROTECTED] > Sent: Wednesday, July 12, 2006 11:14 PM > To: [email protected] > Subject: [R] shapiro.test() output > > R Users: > > My question is probably more about elementary statistics than the > mechanics of using R, but I've been dabbling in R (version 2.2.0) and > used it recently to test some data . > > I have a relatively small set of observations (n = 12) of arsenic > concentrations in background groundwater and wanted to test my > assumption of normality. I used the Shapiro-Wilk test (by calling > shapiro.test() in R) and I'm not sure how to interpret the output. > Here's the input/output from the R console: > > >As = c(13, 17, 23, 9.5, 20, 15, 11, 17, 21, 14, 22, 13) > >shapiro.test(As) > > Shapiro-Wilk normality test > > data: As > W = 0.9513, p-value = 0.6555 > > How do I interpret this? I understand, from poking around the internet, > that the higher the W statistic the "more normal" the data. > > What is the null hypothesis - that the data is normally distributed? > > What does the p-value tell me? 65.55% chance of what - getting > W-statistic greater than or equal to 0.9513 (I picked this up from the > Dalgaard book, Introductory Statistics with R, but its not really > sinking in with respect to how it applies to a Shipiro Wilk test).? > > The method description - retrieved using ?shapiro.test() - is a bit > light on details. > > Thanks much.
The null hypothesis: the data is normally distributed. If p-value > \alpha (significance level) it means that there is no evidence to reject null hypothesis. Otherwise you reject - your data is not normally distributed. ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
