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**F-VALUE=S1 ^{2}/S2^{2}**

**Where,**

S1^{2} is the variance of the first set of values and

S2^{2} is the variance of the second set of values;

F-test refers to any statistical test in which the test statistic has an F-distribution under the null hypothesis. In short, f-test is the ratio of two mean squares. The F Test is based on the F Distribution. F-test is mostly used for comparing the statistical models that have been fir to a data set to identify the model that best fits the population from which the data were sampled.

An F test is normally a test for the joint hypothesis that a number of coefficients are zero. Examples of F-Test includes the following:

- The hypothesis that the means of multiple normally distributed populations, all having the same standard deviation, are equal. This is perhaps the most well-known of hypotheses tested by means of an F-test and the simplest problem in the analysis of variance (ANOVA).
- The hypothesis that the standard deviations of two normally distributed populations are equal, and thus that they are of comparable origin.

* Example*:

Enter first set of values (Eg:2,3,4,5) = 2,4,1,3

Enter second set of values (Eg:4,5,6,7) = 1,4,2,3

* Solution*:

F-VALUE=S1