We covered huge ground in this chapter. By now, you should be up to speed on some of the most common statistical tests. More importantly, you should have a solid grasp of the theory behind NHST and why it works. This knowledge is far more valuable than mechanically memorizing a list of statistical tests and clues for when to use each.
You learned that NHST has its origin in testing whether a weird lady's claims about tasting tea were true or not. The general procedure for NHST is to define your null and alternative hypotheses, define and calculate your test statistic, determine the shape and parameters of the sampling distribution of that test statistic, measure the probability that you would observe a test statistic as or more extreme than the one we observed (this is the p-value), and determine whether to reject or fail to reject the null hypothesis based on the whether the p-value was below or above the alpha level.
You then learned about one-tailed tests versus two-tailed tests...