When using the Chi Square Test, the probability of a Type I error is equal to the significance level.
The test is only an approximate test, so the actual probability of a Type I error will be somewhat different from the significance level.
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Although in some circumstances this is true, it is more often false.
Typically, the Chi Square Test results in more Type I errors than the significance level.
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The Yates correction generally results in a Type I error rate closer to the significance level than the uncorrected Chi Square Test.
Usually the Type I error rate with the correction is much lower than the significance level.
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When the null hypothesis is false, the Yates correction leads to more frequent rejections of the null hypothesis than the uncorrected Chi Square Test.
The correction is conservative and therefore leads to fewer rejections.
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