How should we reason in science? Jan Sprenger and Stephan Hartmann offer a refreshing take on classical topics in philosophy of science, using a single key concept to explain and to elucidate manifold aspects of scientific reasoning. They present good arguments and good inferences as beingcharacterized by their effect on our rational degrees of belief. Refuting the view that there is no place for subjective attitudes in "objective science", Sprenger and Hartmann explain the value of convincing evidence in terms of a cycle of variations on the theme of representing rational degrees ofbelief by means of subjective probabilities (and changing them by Bayesian conditionalization). In doing so, they integrate Bayesian inference - the leading theory of rationality in social science - with the practice of 21st century science.Bayesian Philosophy of Science thereby shows how modeling such attitudes improves our understanding of causes, explanations, confirming evidence, and scientific models in general. It combines a scientifically minded and mathematically sophisticated approach with conceptual analysis and attention tomethodological problems of modern science, especially in statistical inference, and is therefore a valuable resource for philosophers and scientific practitioners.
However, they are not appropriate for all applications. Over the past six years or so, teams of researchers led by Jim Smith have established a strong theoretical underpinning for CEGs. This book
This book brings the power of modern Bayesian thinking, modeling, and computing to a broad audience.
Bayesian Data Analysis, Third Edition
Provides a thorough and rigorous introduction to Bayesian analysis and expert judgment, before moving to more technical content focusing on including stress testing and risk aggregation.
Bayesian Adaptive Methods for Phase I Clinical Trials
Introduction to Probability and Mathematical Statistics . ... Tables of the Ordinates and Probability Integral of the Distribution of the Correlation Coefficient in Small Samples . ... Guide to Tables in Mathematical Statistics .
Unleash the power and flexibility of the Bayesian framework About This Book Simplify the Bayes process for solving complex statistical problems using Python; Tutorial guide that will take the you through the journey of Bayesian analysis ...
' The New York Times Book Review 'In this important book, Nate Silver explains why the performance of experts varies from prescient to useless and why we must plan for the unexpected.
The Signal and the Noise …in 30 Minutes is the essential guide to quickly understanding the fundamental components of prediction outlined in Nate Silver’s bestselling book, The Signal and the Noise: Why So Many Predictions Fail ¬– ...