Quick update on today’s lecture

In addition to the additional reading on F-statistics that I already provided in the lecture detail associated with today’s lecture, I just added a link to an R notebook that delves a bit more into how Bayesian inference is typically implemented and that illustrates a bit better how the likelihood, prior, and posterior are related to one another. We’ll spend some time exploring these ideas at the start of today’s lecture

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