Statistics has many peculiarities and paradoxes that are the inevitable result of using methods derived from the Neyman–Pearson and/or significance-testing paradigms for purposes of representing and interpreting statistical data as evidence. In the light of the new likelihood paradigm we can understand the peculiarities and resolve the paradoxes. In this chapter we look at some conspicuous examples.