Bayesian Logical Data Analysis For The Physical Sciences A Comparative Approach With Mathematica Support Pc Gregory by P.c. Gregory 9780521841504, 052184150X instant download after payment.

Increasingly, researchers in many branches of science are coming into contact with
Bayesian statistics or Bayesian probability theory. By encompassing both inductive
and deductive logic, Bayesian analysis can improve model parameter estimates by
many orders of magnitude. It provides a simple and unified approach to all data
analysis problems, allowing the experimenter to assign probabilities to competing
hypotheses of interest, on the basis of the current state of knowledge.
This book provides a clear exposition of the underlying concepts with large
numbers of worked examples and problem sets. The book also discusses numerical
techniques for implementing the Bayesian calculations, including an introduction
to Markov chain Monte Carlo integration and linear and nonlinear least-squares
analysis seen from a Bayesian perspective. In addition, background material is
provided in appendices and supporting Mathematica notebooks are available from
www.cambridge.org/052184150X, providing an easy learning route for upperundergraduate, graduate students, or any serious researcher in physical sciences
or engineering.
P HIL GREGORY is Professor Emeritus at the Department of Physics and
Astronomy at the University of British Columbia.