The Chisquare test is based upon a normal approx of the (essentially) binomial distribution for the data in question. Small EXPECTED (not observed) values (<5) suggest a asymetric distribution and potential errors in inferential conclusions. The alternative is the exact test, which calculates the exact probabilities of the observed distribution, or a more extreme one, given the constraining expectations.
It is usually much more useful to make the statistics fit the data question than to assume or force the vice versa. --Bob Porter, Tampa > Hi, > In the chisq.test(), if the expected frequency for some categories is <5, there will be a warning message which says > Warning message: > Chi-squared approximation may be incorrect in: chisq.test(x, p = probs) > > I am wondering whether there are some methods to get rid of this mistake... Seems the ?chisq.test() doesn't provide more > options to solve this problem. Or, the only choice is to preprocess the data to avoid this situation? > > Thanks a lot! > > aprilsun ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
