
Probability
An Introduction
Oxford University Press
2nd Edition
Published on 21. August 2014
Book
Paperback/Softback
288 pages
978-0-19-870997-8 (ISBN)
Description
Probability is an area of mathematics of tremendous contemporary importance across all aspects of human endeavour. This book is a compact account of the basic features of probability and random processes at the level of first and second year mathematics undergraduates and Masters' students in cognate fields. It is suitable for a first course in probability, plus a follow-up course in random processes including Markov chains.
A special feature is the authors' attention to rigorous mathematics: not everything is rigorous, but the need for rigour is explained at difficult junctures. The text is enriched by simple exercises, together with problems (with very brief hints) many of which are taken from final examinations at Cambridge and Oxford.
The first eight chapters form a course in basic probability, being an account of events, random variables, and distributions - discrete and continuous random variables are treated separately - together with simple versions of the law of large numbers and the central limit theorem. There is an account of moment generating functions and their applications. The following three chapters are about branching processes, random walks, and continuous-time random processes such as the Poisson process. The final chapter is a fairly extensive account of Markov chains in discrete time.
This second edition develops the success of the first edition through an updated presentation, the extensive new chapter on Markov chains, and a number of new sections to ensure comprehensive coverage of the syllabi at major universities.
A special feature is the authors' attention to rigorous mathematics: not everything is rigorous, but the need for rigour is explained at difficult junctures. The text is enriched by simple exercises, together with problems (with very brief hints) many of which are taken from final examinations at Cambridge and Oxford.
The first eight chapters form a course in basic probability, being an account of events, random variables, and distributions - discrete and continuous random variables are treated separately - together with simple versions of the law of large numbers and the central limit theorem. There is an account of moment generating functions and their applications. The following three chapters are about branching processes, random walks, and continuous-time random processes such as the Poisson process. The final chapter is a fairly extensive account of Markov chains in discrete time.
This second edition develops the success of the first edition through an updated presentation, the extensive new chapter on Markov chains, and a number of new sections to ensure comprehensive coverage of the syllabi at major universities.
More details
Edition
2nd Revised edition
Language
English
Place of publication
Oxford
United Kingdom
Target group
Professional and scholarly
Edition type
Revised edition
Product notice
Paperback (trade)
Unsewn / adhesive bound
Illustrations
24 b/w line drawings
Dimensions
Height: 246 mm
Width: 172 mm
Thickness: 22 mm
Weight
487 gr
ISBN-13
978-0-19-870997-8 (9780198709978)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

E-Book
08/2014
2nd Edition
OUP eBook
€37.99
Available for download

E-Book
08/2014
2nd Edition
OUP eBook
€37.99
Available for download
Persons
Geoffrey Grimmett is Professor of Mathematical Statistics at the University of Cambridge and Master of Downing College, Cambridge. His research interests lie in disordered physical systems, including percolation and related processes. He has written numerous research articles in probability theory and statistical mechanics, as well as three research books and two successful textbooks on probability and random processes at the undergraduate and postgraduate levels.
Dominic Welsh is Professor Emeritus of Mathematics at the University of Oxford and Emeritus fellow of Merton College, Oxford. He held the John von Neumann Professorship at Bonn in 1990-91, and was appointed Professor of Mathematics at Oxford in 1993. His research interests include combinatorics and complexity theory, and he has written more than a hundred papers in these areas. He retired from Oxford University in 2005, and has since then held visiting positions in New Zealand and Barcelona.
Dominic Welsh is Professor Emeritus of Mathematics at the University of Oxford and Emeritus fellow of Merton College, Oxford. He held the John von Neumann Professorship at Bonn in 1990-91, and was appointed Professor of Mathematics at Oxford in 1993. His research interests include combinatorics and complexity theory, and he has written more than a hundred papers in these areas. He retired from Oxford University in 2005, and has since then held visiting positions in New Zealand and Barcelona.
Author
Professor of Mathematical StatisticsProfessor of Mathematical Statistics, University of Cambridge
Professor of Mathematics (retired)Professor of Mathematics (retired), University of Oxford
Content
PART A BASIC PROBABILITY; PART B FURTHER PROBABILITY