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.
If the null is true then the data should appear a certain way. The data does not appear that way. Therefore the null is false. For many types of processes, the concern is that the effect you believe should exist is an illusion. If your belief is z>5 then you test z<=5. Your null is always the opposite of what you believe is the truth. If you cannot falsify the null then you have no knowledge at all, but if you can falsify the null then you can exclude it to some degree of statistical confidence. The original use of the no effect hypothesis was to test whether or not Mendel's laws are true. To do so, it was assumed they were false. In effect any other explanation including creationism and intelligent design were in the null. The null included any explanation that rejected Mendel's laws.