Bayesian Logical Data Analysis for the Physical Sciences: A Comparative Approach with Mathematica SupportBayesian inference provides a simple and unified approach to data analysis, allowing experimenters to assign probabilities to competing hypotheses of interest, on the basis of the current state of knowledge. By incorporating relevant prior information, it can sometimes improve model parameter estimates by many orders of magnitude. This book provides a clear exposition of the underlying concepts with many worked examples and problem sets. It also
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Bayesian Logical Data Analysis for the Physical Sciences: A Comparative Approach with Mathematica Support