I'm still confused as to why it is often recommended to use an independent samples T-Test when comparing two means rather than a One-way Anova.
If t^2 = F, and the p values are the same, why use a T-Test? What is the difference?
I've read that its because a T-Test 'is more flexible', but why is this the case? Is it just because the T distribution is two-tailed, whereas the F distribution is one-tailed?