2009/04/07 by Ben O’Neill · 1 citation
Computer Science · Decision Sciences · Economics, Econometrics and Finance · #Bayesian Modeling and Causal Inference #Forecasting Techniques and Applications #Complex Systems and Time Series Analysis
paper · pdf · doi:10.1111/j.1751-5823.2008.00059.x
openalex publication_date 2009/04/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29
Summary We examine the difference between Bayesian and frequentist statistics in making statements about the relationship between observable values. We show how standard models under both paradigms can be based on an assumption of exchangeability and we derive useful covariance and correlation results for values from an exchangeable sequence. We find that such values are never negatively correlated, and are generally positively correlated under the models used in Bayesian statistics. We discuss the significance of this result as well as a phenomenon which often follows from the differing methodologies and practical applications of these paradigms – a phenomenon we call Bayes' effect.