PSY 350 Lecture Notes - Lecture 35: Squared Deviations From The Mean, Analysis Of Variance, Test Statistic
Document Summary
Another way to write test statistic in anova . F= (variance among sample means)/(variance expected with no treatment effect)= (between-groups variance)/(within-groups variance) The logic of anova is the variance shows up in both places, but the difference is the systematic part, and the systematic differences are what show up in anova. = (systematic group differences+random, unsystematic variability)/(random, unsystematic variability) Under h0, systematic group differences = 0, so: This means that when h0 is true, f is very close to 1. 0. When h0 is not true, f should be substantially larger than 1. 0. Just like the t and z statistics, we know the probability of various f values under h0, and so we can test how likely it is that the f we obtained would have come from that (null) distribution. Degrees of freedom are a little more complex. Explain the overall logic of the anova framework. Calculate and interpret an f statistic for a one-way anova.
