Hello, I want to do normality test on my data I write this but I don't understand the display of the results ks.test(data,"pnorm") In fact I want to know if my data is a normal distribution. I have to check the p-value or D? Thanks. _____________________________________________________________________________ l [[alternative HTML version deleted]]
elyakhlifi mustapha wrote:> > Hello, > I want to do normality test on my data > I write this but I don't understand the display of the results > > ks.test(data,"pnorm") > > In fact I want to know if my data is a normal distribution. I have to > check the p-value or D? > Thanks. > >Example:> r = rnorm(100) > ks.test(r,"pnorm")One-sample Kolmogorov-Smirnov test data: r D = 0.1248, p-value = 0.08874 alternative hypothesis: two-sided Interpretation: the probability of a D value this far from 0 (i.e., abs(D)>=0.1248) is p=0.088 under the null hypothesis that the data are normally distributed. Hence, we would fail to reject the null hypothesis at the "usual" alpha=0.05 level. You might want to consider shapiro.test instead/in addition. Ben Bolker -- View this message in context: http://www.nabble.com/ks.test-tf4820384.html#a13792656 Sent from the R help mailing list archive at Nabble.com.
Hello, I want to do a normality test to know if "donnees" is defined as a normal distribution. To do that I can use the ks.test() function but I can't understand the results. I writed that: ks.test(donnees,"pnorm",mean(donnees),sd(donnees)) and the results are: One-sample Kolmogorov-Smirnov test data: donnees D = 0.0421, p-value < 2.2e-16 alternative hypothesis: two-sided Warning message: cannot compute correct p-values with ties in: ks.test(donnees, "pnorm", mean(donnees), sd(donnees)) _____________________________________________________________________________ l [[alternative HTML version deleted]]