1 Black sea bass (Centropristis striata), whose range is the eastern coast of the United States. 2  Genus Caesioperca. 3  Butterfly perch (Caesioperca lepidoptera), found in the eastern Indian Ocean, and southwest Pacific Ocean including southern Australia and New Zealand. Black sea bass (Centropristis striata), whose range is the eastern coast of the United States. 2  Genus Caesioperca. 3  Butterfly perch (Caesioperca lepidoptera), found in the eastern Indian Ocean, and southwest Pacific Ocean including southern Australia and New Zealand.
The F ratio is drawn from a distribution. If we assume the null hypothesis is true we get one distribution, and if we assume that it is false with various assumptions about effect size, sample size, and so forth we get another distribution. We then do a study and get an F value. When the null hypothesis is false, it is still possible to get an F ratio less than one. The larger the population effect size is (in combination with sample size), the more the F distribution will move to the right, and the less likely we will be to get a value less than one.
F Value and Prob(F) The F value'' and Prob(F)'' statistics test the overall significance of the regression model. Specifically, they test the null hypothesis that all of the regression coefficients are equal to zero. This tests the full model against a model with no variables and with the estimate of the dependent variable being the mean of the values of the dependent variable. The F value is the ratio of the mean regression sum of squares divided by the mean error sum of squares. Its value will range from zero to an arbitrarily large number. The value of Prob(F) is the probability that the null hypothesis for the full model is true (i.e., that all of the regression coefficients are zero). For example, if Prob(F) has a value of 0.01000 then there is 1 chance in 100 that all of the regression parameters are zero.