[R] Chi-squared test when observed near expected

[William Dunlap]

> > 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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