In this section, we delve into some of the deeper theory of estimation and hypothesis testing, including:

• finding statistics that are sufficient for a parameter
• defining the power of a hypothesis test
• determining the sample size necessary for conducting a "powerful" hypothesis test
• investigating the properties a "good" hypothesis test should possess
• defining and deriving likelihood ratio tests

We also get some practice on choosing an appropriate statistical method for analyzing a given set of data.