heavy-tailed samples have implications for the central limit theorem, which says that in samples of 30 or more the sampling distribution should be normal (Section 6.6.1); for heavy-tailed distributions samples need to be much larger, up to 160 in some cases (Wilcox, 2010). To sum up, F is not robust, despite what your supervisor might tell you.
