In large samples, Yates's continuity correction for the chi-square test tends to be:

In large samples, Yates's continuity correction for the chi-square test tends to be:

• A. Little difference in results.
• B. Substantial difference in results.
• C. Dramatically alter the degrees of freedom.
• D. Required for validity.

Answer: (A)

The idea being tested is how Yates's continuity correction behaves as sample size grows. Yates correction adjusts the chi-square statistic in 2x2 tables to account for discreteness, subtracting 0.5 from the absolute difference between observed and expected counts before squaring. This makes the test more conservative when counts are small. As the sample gets large, the observed and expected counts become large and the discreteness of individual counts matters less. The correction then has an vanishing effect, so the corrected and uncorrected chi-square statistics produce almost the same p-value. That’s why, in big samples, results are very similar whether you apply the continuity correction or not.

The idea being tested is how Yates's continuity correction behaves as sample size grows. Yates correction adjusts the chi-square statistic in 2x2 tables to account for discreteness, subtracting 0.5 from the absolute difference between observed and expected counts before squaring. This makes the test more conservative when counts are small.

As the sample gets large, the observed and expected counts become large and the discreteness of individual counts matters less. The correction then has an vanishing effect, so the corrected and uncorrected chi-square statistics produce almost the same p-value. That’s why, in big samples, results are very similar whether you apply the continuity correction or not.