Seminal Ideas & Controversies in Statistics

Catalog description

This graduate-level seminar explores the driving forces behind modern statistical thought by engaging directly with foundational papers and debates that have shaped the field. Anchored in Roderick Little’s Seminal Ideas and Controversies in Statistics, the course emphasizes conceptual understanding and historical context rather than formal proofs. Three central themes structure the semester: 1. Philosophical Foundations of Inference • Likelihood principle • Bayesian vs. frequentist paradigms • Fisher’s fiducial inference • Hypothesis testing debates (Fisher vs. Neyman–Pearson) 2. Methodological Developments • Regression and shrinkage estimation • Multiple comparisons • Robust inference methods 3. Statistical Design & Randomization • Experimental design foundations • Randomization as the basis of inference • Modern perspectives on causal estimation Students will analyze seminal and modern papers, present key controversies, and articulate their relevance to contemporary statistical practice. Recommended Prerequisites: Graduate-level courses in probability, statistical inference, and regression.