What's the difference between an F-Test and T-Test?

F-test and T-test are the two statistical test used for hypothesis testing. They assist the researchers to decide whether to accept the null hypothesis or reject it. The differences between T-test and F-test are as follows.

F-test

The F-test is usually used to compare the two standard deviations of two samples and check the variability. F-test is always carried out as a single-sided test as variance cannot be negative. Under the null hypothesis, the F-statistic follows the Snedecor’s F-distribution. The F-test can be applied on the large sampled population.

T-test

The T-test is used to compare the means of two different sets. It says whether the mean of one group is significantly different from the other group. T-test can be either paired and normal. It is generally used to calculate numerical data. Under the null hypothesis, T-test is based on Student t-distribution. The T-test is used when the sample population is small and the sample on which the test was priory applied remains the same.