Find Critical Value of F for F-Test

Fisher's F-distribution table & how to use instructions to quickly find the critical value of F at a stated level of significance (α = 1%, 2.5%, 5%, 10% & 95% or α = 0.01, 0.025, 0.5, 0.1 & 0.95) for the test of hypothesis in statistics & probability surveys or experiments to analyze two or more variances simultaneously. The degrees of freedom is used to refer the F-table values for the specified level of significance such as 1%, 2%, 3%, 5%, 10% etc. It's generally represented by F_e. Critical value of F from t-distribution table represents the rejection area of distribution. The estimated value of F or F-statistic (F₀) is compared with the critical value of F from F-distribution table to check the significance of results. For locating the F_e (critical value of F) in the table quickly, users can supply the values of degrees of freedom (df) and significance level (α) directly in the above interface. This F-table to find the critical value of F is also available in pdf format too, users may download this table in pdf format to refer it later offline.

How to Find Critical Region in F-Test

Users may use this below F-table calculator or refer the rows & columns value of t-distribution table for a stated level of significance to find the critical region of F-distribution.
by Using Calculator
Supply or select the values of degrees of freedom (df) m & n, and significance level (α) directly to the F-table calculator and hit on "LOCATE" to address the corresponding critical value of F.

by Using F-Distribution Table
Refer the row & column meeting point of m & n degrees of freedom at a specified level of significance (α = 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). The point where the row & column meets for the corresponding input value is the critical value of F or the rejection area of F-distribution.

Inference

The below statements show when to accept or reject null hypothesis H₀ in F-test

For null hypothesis H₀ :
If F₀ < F_e then the null hypothesis H₀ is accepted.
It states that there is no significance difference between F-statistic & expected value of F.

If F₀ > F_e then the null hypothesis H₀ is rejected.
It states that there is significance difference between F-statistic & expected value of F.