Bianca Vieru- Dimulescu wrote: > Hello, > > I'm trying to calculate a chi-squared test to see if my data are > different from the theoretical distribution or not: > > chisq.test(rbind(c(79, 52, 69, 71, 82, 87, 95, 74, 55, 78, 49, > 60),c(80,80,80, 80, 80, 80, 80, 80, 80, 80, 80, 80))) > > Pearson's Chi-squared test > > data: rbind(c(79, 52, 69, 71, 82, 87, 95, 74, 55, 78, 49, 60), c(80, > 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80)) > X-squared = 17.6, df = 11, p-value = 0.09142 > > Is this correct? If I'm doing the same thing using Excel I obtained a > different value of p.. (1.65778E-14) > > Thanks a lot, > Bianca
It would be unusual to have 12 observed frequencies all equal to 80. So I'm guessing that you have a 12-category variable and want to test its fit to a discrete uniform distribution. I assume that your frequencies are x <- c(79, 52, 69, 71, 82, 87, 95, 74, 55, 78, 49, 60) Then just use chisq.test(x) (see the help page). (If those 80's are expected cell frequencies, they should sum to sum(x) = 851.) I don't know what Excel does. Peter Peter Ehlers University of Calgary > > ______________________________________________ > [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 ______________________________________________ [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
