In the kind of statistician networks I participate in, there's a huge debate on whether introductory statistics curricula need a profound overhaul. In the particular circles I run in, there's a big movement to shift away from the NHST methods I spoke about in Chapter 6, Testing Hypotheses, in favor of either the Bayesian methods we discussed in the previous chapter, or resampling methods such as the bootstrap that we'll be discussing in this chapter.
In spite of my personal ideas on the matter, preferences, and current workflow tendencies, I strongly felt that I would be doing you, dear reader, an enormous disservice leaving out such staples of data analysis as ANOVA and the Student's t-test, especially if you want to make a career of this. For better or worse, the vast majority of new research in science still makes strong use of the techniques...
