Yates Correction
This article covers meaning & overview of Yates Correction from statistical perspective.
What is Yates Correction?
Yate’s correction, also known as Yate’s chi-squared test, is used to test independence of events in a cross table i.e. a table showing frequency distribution of variables. It is used to test if a number of observations belonging to different categories validate a null hypothesis. It is a correction made to chi-square values in a binomial frequency distribution table.
It considers that the discrete probability of these frequencies is very near to continuous chi-squared distribution.However, to reduce the error in the assumption, a correction for continuity was suggested by Frank Yates. It is done by reducing the difference between each observed value and its expected value in a binomial frequency table by 0.5. These tests are commonly used when expected frequencies are less than ten.
Formula : XYates2 = ∑(│Oi –Ei│- 0.5)2/Ei
Eg -
|
|
Sample A |
Sample B |
|
O |
80 |
40 |
|
E |
79.8 |
40.2 |
|
O-E |
0.2 |
-0.2 |
|
(O-E)^2 |
0.04 |
0.04 |
XYates2 = 0.0015
These tests are commonly used in diagnostics, environmental sciences, biology, etc.
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