Probability Essentials from Booth PhD Math Camp
Today at Booth’s PhD math camp, we revisited some foundational concepts in probability theory. Two key topics stood out to me: Frequentist vs. Bayesian Perspectives A crucial distinction lies in what we treat as random: Frequentist: Parameters (e.g., population mean $\mu$) are fixed, and randomness comes from the data. Example: $$ P(X \mid \mu) $$ We ask: Given a true mean $\mu$, how likely is it to observe sample mean $X$?...