Description
Book Synopsis
An update of this popular introduction to probability theory and information theory with new material on Markov chains.
Trade Review
Reviews for the first edition: 'I found the book interesting and entertaining … The level of difficulty of the material is well judged …' D. A. Stephens, The Statistician
'This text provides a blend of the traditional disciplines of probability theory and the relatively new field of information science in a well written manner … the author succeeds in introducing concepts of probability theory gently paced and user friendly as stated on page xi of the preface … The blend of probability theory and information science makes this an innovative text... The innovative blend of probability theory and information theory make this text a good choice for teachers wanting to present both a traditional background and modern ideas to their students.' Journal of the American Statistical Association
'Reviewing this book was a pleasure. Clearly the author is delighted by his subject and this attitude is communicated well … this is an excellent book which will make a stimulating text for Honours courses in probability for applied mathematicians, statisticians, physicists or engineers' John M. Halley, The Statistician
'… a nice introductory text for a modern course on basic facts in the theory of probability and information. The author always has in mind that many students, especially those specializing in informatics and/or technical sciences, do not often have a firm background in traditional mathematics. Therefore he attempts to keep the development of material gently paced and user-friendly.' EMS Newsletter
Table of Contents
Preface to the first edition; Preface to the second edition; 1. Introduction; 2. Combinatorics; 3. Sets and measures; 4. Probability; 5. Discrete random variables; 6. Information and entropy; 7. Communication; 8. Random variables with probability density functions; 9. Random vectors; 10. Markov chains and their entropy; Exploring further; Appendix 1. Proof by mathematical induction; Appendix 2. Lagrange multipliers; Appendix 3. Integration of exp (-½x²); Appendix 4. Table of probabilities associated with the standard normal distribution; Appendix 5. A rapid review of Matrix algebra; Selected solutions; Index.
