On 21/02/17 23:47, Jomy Jose wrote:
I tried to do chi square test for the following observed frequencies
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A B
A 8 4
B 12 10
R gave the following output:
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Pearson's Chi-squared test with Yates' continuity correction
data: M
X-squared = 0.10349, df = 1, p-value = 0.7477
Warning message:
In chisq.test(M) : Chi-squared approximation may be incorrect
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Whether this result can be relied or we have to use Fishers exact test ?
(a) With a p-value of 0.7477 there is no evidence against the null
hypothesis no matter how you slice it.
(b) To assuage your trepidations, use "simulate.p.value=TRUE".
E.g.
chisq.test(M,simulate.p.value=TRUE,B=9999)
Note that the value of X-squared that is returned is "of course" the
same as what you'd get by setting correct=FALSE. I got a p-value of
0.7178; you will get something slightly different, since a simulated
p-value is random, but it will be about 0.71 or 0.72.
Bottom line: Don't reject H_0!!!
cheers,
Rolf Turner
--
Technical Editor ANZJS
Department of Statistics
University of Auckland
Phone: +64-9-373-7599 ext. 88276
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