F test: Theory, Solved Example and Demonstration in Agri Analyze
The blog discuss in details about theory of F test, its use cases, solved example (manually) and a demonstration using online tool Agri Analyze (Reading time 10 min) Introduction The F-test is a statistical method used to compare the variances of two samples or the ratio of variances across multiple samples. It assesses whether the data follow an F-distribution under the null hypothesis, assuming standard conditions for the error term (ε). The test statistic, denoted as F, is commonly used to compare fitted models to determine which best represents the underlying population. F-tests are frequently employed in models fitted using least squares. The test is named after Ronald Fisher, who introduced the concept as the "variance ratio" in the 1920s, with George W. Snedecor later naming the test in Fisher’s honor. Definition An F-test uses the F-statistic to evaluate whether the variances of two samples (or populations) are equal. The test assumes that the population follows an