F Test Formula

A test statistic which has an F-distribution under the null hypothesis is called an F test. It is used to compare statistical models as per the data set provided or available. George W. Snedecor, in honour of Sir Ronald A. Fisher, termed this formula as F-test Formula.

\[\LARGE F \; Value \; = \; \frac{Variance \; of \;set \; 1}{Variance \; of \; set \; 2} = \frac{\sigma _{1}^{2}}{\sigma _{2}^{2}}\]

To compare the variance of two different sets of values, the F test formula is used. To be applied to F distribution under the null hypothesis, we first need to find out the mean of two given observations and then calculate their variance.

\[\LARGE \sigma^{2}\; = \; \frac{\sum (x – \overline{x})^{2}}{n-1}\]

σ2 = Variance
x = Values given in a set of data

\(\begin{array}{l}\overline{x}\end{array} \)
= Mean of the data
n = Total number of values

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