The F-test in ANOVA is an example of an omnibus test, which tests the overall significance of the model. A significant F test means that among the tested means, at least two of the means are significantly different, but this result doesn't specify exactly which means are different one from the other. Actually, testing means' differences is done by the quadratic rational F statistic ( F=MSB/MSW). In order to determine which mean differs from another mean or which contrast of means are significantly different, Post Hoc tests (Multiple Comparison tests) or planned tests should be conducted after obtaining a significant omnibus F test. It may be considered to use the simple Bonferroni correction or another suitable correction.