Introduction to Probability and Statistics from a Bayesian Viewpoint, Part 1, Probability
D. V. Lindley(Author)
Cambridge University Press
Published on 2. January 1965
Book
Hardback
272 pages
978-0-521-05562-8 (ISBN)
Article exhausted; check for reprint
Description
The two parts of this book treat probability and statistics as mathematical disciplines and with the same degree of rigour as is adopted for other branches of applied mathematics at the level of a British honours degree. They contain the minimum information about these subjects that any honours graduate in mathematics ought to know. They are written primarily for general mathematicians, rather than for statistical specialists or for natural scientists who need to use statistics in their work. No previous knowledge of probability or statistics is assumed, though familiarity with calculus and linear algebra is required. The first volume takes the theory of probability sufficiently far to be able to discuss the simpler random processes, for example, queueing theory and random walks. The second volume deals with statistics, the theory of making valid inferences from experimental data, and includes an account of the methods of least squares and maximum likelihood; it uses the results of the first volume.
More details
Language
English
Place of publication
Cambridge
United Kingdom
Target group
College/higher education
Weight
480 gr
ISBN-13
978-0-521-05562-8 (9780521055628)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions

D. V. Lindley
Introduction to Probability and Statistics from a Bayesian Viewpoint, Part 1, Probability
Book
03/1980
Cambridge University Press
€63.70
Shipment within 15-20 days
Additional editions

D. V. Lindley
Introduction to Probability and Statistics from a Bayesian Viewpoint, Part 1, Probability
Book
03/1980
Cambridge University Press
€63.70
Shipment within 15-20 days
Content
1. Probability; 2. Probability distributions: one variable; 3. Probability distributions: several variables; 4. Stochastic processes.