I What is Yates' correction of contingency?

AI Thread Summary
Yates' correction for continuity is applied in chi-squared tests to adjust for continuity when dealing with discrete data. Specifically, it involves subtracting 0.5 from the absolute difference between observed and expected values when degrees of freedom (df) equals 1. This correction aims to improve the accuracy of the test results, although it is not widely favored among statisticians. Many prefer to combine categories with fewer than five observations instead of using Yates' correction. Understanding this method can enhance the interpretation of chi-squared tests in statistical analysis.
Tyto alba
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I can't understand a word of Wikipedia.[/PLAIN]

P.S. What I know so far is subtracting 0.5 from O-E if df=1 in Goodness of fit (?) is Yates' correction.
 
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Yates correction is simply what it says it is, which is you take the absolute difference between the observed and expected value and subtract 0.5. It isn't very popular with many people preferring merging cells that have less than 5 into one bucket.
 
I couldn't edit my question so I posted a new one. Please take a look.
 

Thread 'Deductive proof in logic formal systems'

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