A colleague was using three pair-wise t-tests plus Bonferroni correction to detect any differences in the means of three groups. My first response was to tell him to use an ANOVA instead, since my understanding is that's the "correct" way to detect a difference in means between 3 or more groups.
However, if multiple comparisons are being controlled for, as they were in his case, is the ANOVA still best? Does it depend on the context?
(To test, I made a quick simulation of 3 distributions of uniformly distributed random numbers, applying a variable offset to the mean of one of the groups. Using a Bonferroni correction the two methods were almost always in agreement (98% of the time for the offsets I used).)