Bayesian Thinking for People Who Hated Statistics

Bayesian reasoning is something humans do intuitively every day, yet statistics courses obscure it with formulas. Using the classic mammogram problem (where 82% of doctors get the wrong answer), the post demonstrates how counting natural frequencies instead of juggling percentages makes Bayes' theorem intuitive. It critiques frequentist statistics and p-value misuse, backed by the ASA's 2016 guidance and the replication crisis. A practical five-step PRIOR framework is introduced for applying Bayesian thinking at work. Real-world applications covered include spam filtering (Paul Graham's 1995 approach), Bayesian hyperparameter optimization, probabilistic programming with PyMC/Stan, and the dramatic search for the USS Scorpion submarine using Bayesian search theory.