The basic test of independence for a table based on the Chi-squared distribution can be done using the `chisq.test` function. This is in the stats package which is installed and loaded by default, so you don't need to do anything additional. There is also the `fisher.test` function for Fisher's exact test (similar hypotheses, different methodology and assumptions, may be really slow on your table).
If you need more than the basics provided in those functions, then a search of CRAN may be helpful, or give us more detail to be able to help. On Thu, Dec 20, 2018 at 12:08 AM km <srikrishnamo...@gmail.com> wrote: > > Dear All, > > How do I do a test of independence with 16x16 table of counts. > Please suggest. > > Regards, > KM > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > 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. -- Gregory (Greg) L. Snow Ph.D. 538...@gmail.com ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.