Comparing Bayesian and Frequent Approaches
9 Mar 2022
A new lecture titled “Two Meanings of Probability” compares Bayesian and Frequentist approaches to estimating parameters of a distribution. Using Python to simulate random draws from a binomial distribution, estimating the parameters using the Frequentist approach is shown to converge to the true parameters by the Law of Large Numbers. Similarly, as a Bayesian observes more random draws from the binomial distribution, they become more confident about the true value of the parameters. The lecture provides several exercises for the reader to test their knowledge of these two approaches to probability.
Published by: Natasha Watkins