Continuity corrections have historically been used to make adjustments to the p-value when a continuous distribution approximates a discrete distribution. Yates correction for the Pearson chi-square (X2) test is probably the most well-known continuity correction. In some cases, the continuity correction may adjust the p-value too far, and the test then becomes overly conservative.
Modern computing power makes such corrections unnecessary, as exact tests that use the discrete distributions are available for moderate and in many cases even large sample sizes. Hirji (Hirji 2005), states "An applied statistician today, in our view, may regard such corrections as interesting historical curiosities."
From the Statistical Reference Guide for Analyse-it 6.24.0: https://analyse-it.com/docs/user-guide/101/continuity-correction
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