[R] Chi-squared test when observed near expected
William Dunlap
wdunlap at tibco.com
Mon Dec 3 23:34:55 CET 2012
> > sum((x$observed-x$expected)^2/x$expected)
> [1] 0.05562457
Read about Yate's continuity correction - your formula does not use it
and chisq.test does unless you suppress it:
> chisq.test(trial)
Pearson's Chi-squared test with Yates' continuity correction
data: trial
X-squared = 0, df = 1, p-value = 1
> chisq.test(trial, correct=FALSE)
Pearson's Chi-squared test
data: trial
X-squared = 0.0556, df = 1, p-value = 0.8136
Bill Dunlap
Spotfire, TIBCO Software
wdunlap tibco.com
> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf
> Of Troy S
> Sent: Monday, December 03, 2012 1:41 PM
> To: r-help at r-project.org
> Subject: [R] Chi-squared test when observed near expected
>
> Dear UseRs,
>
> I'm running a chi-squared test where the expected matrix is the same as the
> observed, after rounding. R reports a X-squared of zero with a p value of
> one. I can justify this because any other result will deviate at least as
> much from the expected because what we observe is the expected, after
> rounding. But the formula for X-squared, sum (O-E)^2/E gives a positive
> value. What is the reason for X-Squared being zero in this case?
>
> Troy
>
> > trial<-as.table(matrix(c(26,16,13,7),ncol=2))
> > x<-chisq.test(trial)
> > x
>
>
>
> data: trial
> X-squared = 0, df = 1, p-value = 1
>
> > x$expected
> A B
> A 26.41935 12.580645
> B 15.58065 7.419355
> >
> > x$statistic
> X-squared
> 5.596653e-31
> > (x$observed-x$expected)^2/x$expected
> A B
> A 0.006656426 0.013978495
> B 0.011286983 0.023702665
> > sum((x$observed-x$expected)^2/x$expected)
> [1] 0.05562457
> >
>
> [[alternative HTML version deleted]]
>
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