Summary
In this chapter, we covered two important methods of parameter estimation: the method of moments and MLE. You then learned the background of MLE, the Bayesian way of modeling the likelihood function, and so on. However, we don't know how well our estimators perform, yet. In general, it requires a pipeline of hypothesis testing with a quantitative argument to verify a claim. We will explore the rich world of hypothesis testing in the next chapter, where we will put our hypotheses/assumptions to the test.
