Why Bayesian Stats Needs Monte-Carlo Methods
Read OriginalThe article explores the necessity of Monte Carlo methods in Bayesian statistics, particularly for problems like comparing Beta distributions in A/B testing. It uses a Twitter discussion about election forecasting probabilities (like Nate Silver's 71% prediction) to illustrate the limitations of analytic solutions and why simulation-based approaches are often the only practical way to solve real-world Bayesian inference problems.
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