Data 145: Evidence and Uncertainty - Topic Map

Created on April 23, 2026

2026   ·   statistics   data145   notes   statistics-inference   ·   technical-blogs

My notes on Data 145: Evidence and Uncertainty. This page is a compact topic map for future review and for anyone else looking for a high-level reference.

Course thread: how to turn noisy data into evidence, quantify uncertainty, and make decisions without pretending randomness disappeared.

Phase 1 Bridge

Data 145 Phase 1 Statistical Inference Notes: From MLE to Neyman-Pearson to Reward Models A long-form roadmap for estimation, Fisher information, bootstrap, hypothesis testing, Neyman-Pearson, and a short bridge to modern AI.

Phase 2 Notes: Topic Map

Phase 2 notes Lectures 14-15: Testing, Confidence, and Power Testing structure, confidence intervals, and power. Phase 2 notes Lectures 17-18: Likelihood and Decision Rules Likelihood reasoning and general testing procedures. Phase 2 notes Lectures 19-20: Multiple Testing Bonferroni, FWER, FDP, and FDR. Phase 2 notes Lectures 21-22: MGFs and Concentration MGFs, Chernoff thinking, Hoeffding, and tail bounds. Phase 2 notes Lectures 23-24: Geometry of Linear Models Rotations, nuisance/signal/residual blocks, t, chi-squared, F, ANOVA, and regression.
Study path: start with the Phase 1 synthesis for the course narrative, then use the Phase 2 pages as topic-by-topic references.


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