Cambridge Atronomy  
  • View basket
  • Help
Home > Astronomy > Bookfair 2008 > Mathematical Tools




Contact College Sales

Mathematical Tools

Mathematical Methods for Physics and Engineering

Mathematical Methods for Physics and Engineering

K. F. Riley, University of Cambridge
M. P. Hobson, University of Cambridge

The third edition of this highly acclaimed undergraduate textbook is suitable for teaching all the mathematics for an undergraduate course in any of the physical sciences. As well as lucid descriptions of all the topics and many worked examples, it contains over 800 exercises. New stand-alone chapters give a systematic account of the 'special functions' of physical science, cover an extended range of practical applications of complex variables, and give an introduction to quantum operators. Further tabulations, of relevance in statistics and numerical integration, have been added. In this edition, half of the exercises are provided with hints and answers and, in a separate manual available to both students and their teachers, complete worked solutions.

Request Examination Copy | Learn more
Practical Statistics for Astronomers

Practical Statistics for Astronomers

J. V. Wall, University of Oxford
C. R. Jenkins, Schlumberger Cambridge Research Ltd

This practical handbook presents the most relevant statistical and probabilistic machinery for use in observational astronomy. Classical parametric and non-parametric methods are covered, but there is a strong emphasis on Bayesian solutions and the importance of probability in experimental inference. The book contains many worked examples, and problems that make use of databases which are available on the Web. It is suitable for self-study at advanced undergraduate or graduate level, as a reference for professional astronomers, and as a textbook basis for courses in statistical methods in astronomy.

Request Examination Copy | Learn more
Bayesian Logical Data Analysis for the Physical Sciences

Bayesian Logical Data Analysis for the Physical Sciences
A Comparative Approach with Mathematica Support

P. C. Gregory, University of British Columbia, Vancouver

Increasingly, researchers in many branches of science are coming into contact with Bayesian statistics or Bayesian probability theory. 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 Markov Chain Monte-Carlo integration and linear and nonlinear least-squares analysis seen from a Bayesian perspective. Background material is provided in appendices and supporting Mathematica notebooks are available. Suitable for upper-undergraduates, graduate students, or any serious researcher in physical sciences or engineering.

Request Examination Copy | Learn more