Notes
- More detailed proof of Kerridge’s law [pdf] [tex] [Kerridge (1963)]
Biographies
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 $\chi^2$
