# F-Test (F_{0}, F_{e} & H_{0}) Calculator

getcalc.com's **F-Test calculator** to estimate F-statistic (F_{0}), critical value (F_{e}) from *F-distribution table* for given degrees of freedom & hypothesis test (H_{0}) to check if the test of significance is accepted or rejected in statistics & *probability *experiments. Users can use this calculator to analyze two or more *variances* together or to generate the complete work with step by step calculation for any corresponding input values to solve grade school F-test worksheet problems.

## Why F-Test & Formula

F-Test is the technique using statistical methods to estimate if the test results are statistically significant by analyzing two or more variances. It requires F-statistic F_{0} & critical (table) value of F-distribution F_{e} at a stated level of significance (α = 1%, 2%, 3%, 4%, 5%, 10%, 25%, 5% etc or α = 0.01, 0.02, 0.03, 0.04, 0.05, 0.1, 0.25, 0.5 etc) for the test of hypothesis (H_{0}) in statistics & probability surveys or experiments to analyze two or more variances simultaneously. Generally, F-test is the ratio between two or more variances to identify the quality of different variances. The estimated value of F or F-statistic (F_{0}) is compared with the critical value from F-distribution table to check the significance of results. Users may use this below F-test calculator to estimate F-statistic (F_{0}), critical value (F_{e}) & hypothesis test (H_{0}) to test the significance between two or more sample variances.**Inference**

The below statements show when to accept or reject null hypothesis H_{0} in F-test__For null hypothesis H _{0} :__

If F

_{0}< F

_{e}then the null hypothesis H

_{0}is accepted.

It states that there is no significance difference between F-statistic & expected or critical value of F.

If F

_{0}> F

_{e}then the null hypothesis H

_{0}is rejected.

It states that there is significance difference between F-statistic & expected or critical value of F.

**Formula :**The below is the mathematical representation for F-test formula to estimate the quality of variances among two or more sample variances to predict the characteristics of population parameters of a unknown distribution.

## Solved Examples with Work - F-Test

The below are the solved examples for F-Test with step by step estimation to analyze two or more variances together. Users may refer the below estimations to know what formula & input parameters are being used in the respective calculation.