Notes

• More detailed proof of Kerridge’s law [pdf] [tex] [Kerridge (1963)]

Biographies

• Life and Work of Statisticians
• Interview with Dennis Lindley
• A Conversation with David Cox

Bayesian statistics

• Kass & Wasserman, The Selection of Prior Distributions by Formal Rules
• Consonni et al, Prior Distributions for Objective Bayesian Analysis
• Gelman et al, Bayesian Data Analysis
• Gelman et al, Regression and Other Stories
• Mackay, Information Theory, Inference, and Learning Algorithms
• Earman, Bayes or Bust
• Bayesian Spectacles
• Kass & Raftery, Bayes factors
• Lavine, Introduction to Statistical Thought
• Lindley, Comment on Harold Jeffreys’s Theory of Probability
• Lindley, Philosophy of Statistics
• Berger, Selected works
• Brewer, Lecture notes and videos
• Loredo, Introduction to Bayesian Inference
• Bernardo, An Introduction to Objective Bayesian Statistics
• [1708.07459] Divergence, Entropy, Information: An Opinionated Introduction to Information Theory
• [2004.06425] Computing Bayes: Bayesian Computation from 1763 to the 21st Century

$p$-values

• Berger & Selke, Testing a Point Null Hypothesis: The Irreconcilability of P Values and Evidence
• Berger & Delampady, Testing Precise Hypotheses
• Lew, Bad statistical practice in pharmacology (and other basic biomedical disciplines): you probably don’t know $P$
• Hubbard & Bayarri, Confusion Over Measures of Evidence ($p$’s) Versus Errors ($\alpha$’s) in Classical Statistical Testing
• Rozeboom, The fallacy of the null-hypothesis significance test
• Benjamin et al, Redefine Statistical Significance
• Gibbons & Pratt, $P$-values: Interpretation and Methodology
• Wagenmakers, A practical solution to the pervasive problems of p values

Confidence intervals

• Morey et al, The fallacy of placing confidence in confidence intervals

Fine-tuning and Occam’s razor

• MacKay, Bayesian methods for adaptive models
• Jeffreys & Burger, Sharpening Ockam’s Razor on a Bayesian Strop
• [0903.4055] Which fine-tuning arguments are fine?
• [1204.4940] Quantified naturalness from Bayesian statistics
• Stanford Encyclopedia of Philosophy, William of Ockham
• Murray, A note on the evidence and Bayesian Occam’s razor

Frequentist statistics for the LHC

• [1005.1891] Trial factors for the look elsewhere effect in high energy physics
• [1310.1284] Discovering the Significance of 5 sigma
• [1007.1727] Asymptotic formulae for likelihood-based tests of new physics
• CDF Statistics Committee Recommendations
• Lyons, Comparing Two Hypothesis. Contains pedagogical discussion of “paradox” that $\Delta\chi^2$ could lead to different conclusions than just $\chi^2$