For example following imaginary dataset of group I-IV containing, ideally gaussian distributed, mortalities. Hypothetical mean value to test against: 0.2

Data set:

Column statistics with t-test against a theoretical mean of 0.2 (p=0.05).

With Bonferroni correction the adjusted p-value would be 0.0125 (4 tests -> 0.05/4=0.0125), therefore the mean of group II does not differ significantly from 0.2 although its t-test p-value is smaller than 0.05.

Can it be done this way (or in a similar way with the FDR approach)?