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Talk:Significance of E. Coli Evolution Experiments (view source)
Revision as of 20:53, March 11, 2009
, 20:53, March 11, 2009Literature on Monte Carlo tests
::You are assuming that p-values are wrong based on a test that is inappropriate in this case due to data limitations. Did you perform a z-transformation on the chi-squared for the three data groups?--[[User:Able806|Able806]] 10:19, 11 March 2009 (EDT)
::You are assuming that p-values are wrong based on a test that is inappropriate in this case due to data limitations. Did you perform a z-transformation on the chi-squared for the three data groups?--[[User:Able806|Able806]] 10:19, 11 March 2009 (EDT)
:::There's a large literature on various kinds of Monte Carlo test, a very short summary of which is that they're inevitably more accurate than parametric tests (e.g. F, t, chi-squared, etc) because they don't make assumptions about the distribution of the data under the null hypothesis. See for example ''Introduction to the Bootstrap'' by B. Efron and R. Tibshirani and ''The Jack-knife, the Bootstrap and Other Resampling Plans'', also by Efron. They're certainly applicable to small datasets and their accuracy is really only limited by the number of samples you care to take. E.g. 1000 M-C samples would give you a pretty accurate idea about significance at the alpha<1% level (That book should answer SJohnson's questions of 18:50 on 4/3/09 and 16:38 on 5/3/09 about accuracy and Aschalfly's comment of 17:07 on 5/3/09 about appropriateness of Monte Carlo tests.) [[User:FredFerguson|FredFerguson]] 16:53, 11 March 2009 (EDT)
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