In this lecture, we start out with Q-Q and P-P probability plots that we did not have time to cover from last time. We then transition to a review about type-I error and p values and try to motivate the topics of STATISTICAL POWER and EFFECT SIZES, which we will dive into more in the next few lectures. We then discuss summary statistics and how to use methods such as maximum likelihood estimation (MLE) to come up with good choices of parameters for distributions picked in the input modeling process. Next time, we will discuss testing the (goodness of) fit for those parameterized distributions.
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