High Quality Content by WIKIPEDIA articles! High Quality Content by WIKIPEDIA articles! In statistics, Yates' correction for continuity (or Yates' chi-square test) is used in certain situations when testing for independence in a contingency table. In some cases, Yates' correction may adjust too far, and so its current use is limited. Using the chi-squared distribution to interpret Pearson's chi-squared statistic requires one to assume that the discrete probability of observed binomial frequencies in the table can be approximated by the continuous chi-squared distribution. This assumption is not quite correct, and introduces some error. To reduce the error in approximation, Frank Yates, an English statistician, suggested a correction for continuity which adjusts the formula for Pearson's chi-square test by subtracting 0.5 from the difference between each observed value and its expected value in a 2 x 2 contingency table. This reduces the chi-square value obtained and thus increases its p-value.

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