A guide to comparing survey sample demographics with national population data using R, covering both classical and Bayesian statistical methods.
Explores the intersection of multiple imputation and probabilistic record linkage, proposing a method to sample link sets for robust statistical analysis.
Explores how Large Language Models perform implicit Bayesian inference through in-context learning, connecting exchangeable sequence models to prompt-based learning.
A data scientist's journey from dogmatic Bayesianism to a pragmatic, 'secular' use of Bayesian tools without requiring belief in the model's literal existence.
A statistical analysis discussing the limitations of confidence intervals, using examples from small-area sampling to illustrate their weak properties.
A guide to six statistical methods (frequentist and Bayesian) for comparing group means, with R and Stan code examples.
Explores Bayesian inference when data strongly contradicts prior expectations, analyzing how heavy-tailed priors and likelihoods affect posterior beliefs.
Analyzing the Monty Hall problem, exploring learning strategies and optimal decisions based on observed game history and host behavior.
Explores Bayesian vs. Frequentist approaches to the multiple comparisons problem in statistical inference and data analysis.
A critique of a proposal to lower the p-value threshold for statistical significance from 0.05 to 0.005, arguing it addresses symptoms, not root causes.
