This article covers meaning & overview of Williams Correction from statistical perspective.
The G Test in statistics is used to find out the goodness of fit for frequency data. This test attempts to find out any difference between an observed frequency distribution and hypothesized frequency distribution. It can be of 2 types:
For 1-way test, the formula is:
G = 2 ∑ O ln O/E
Where O and E are the observed and expected numbers respectively, ln stands for natural logarithm and ∑ denotes summation.
For example, considering the different types of leaves:
|
Leaves |
Thorny |
Smooth |
Dry |
Observed |
12 |
6 |
2 |
2 |
Expected |
3.3 |
5.5 |
5.5 |
7.7 |
Using the above formula we get G = 22.58
Here, the Type 1 error is higher and so Williams suggested that G should be divided by a correction factor, q which is equal to 1 + (c2-1)/6 n v where c = no: of categories, n = total no: of observations and v = degrees of freedom ( c-1).
For the above example, q= 1 + 8/396 = 1.02
Gadjusted = 22.58/1.02 = 22.13
This article has been researched & authored by the Business Concepts Team which comprises of MBA students, management professionals, and industry experts. It has been reviewed & published by the MBA Skool Team. The content on MBA Skool has been created for educational & academic purpose only.
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