Modern Probability Theory and Its Applications
Will be published approx. on 2. April 1992
Book
Paperback/Softback
480 pages
978-0-471-57278-7 (ISBN)
Description
Mathematical probability theory is especially interesting to scientists and engineers. It introduces probability theory, showing how probability problems can be formulated mathematically to systematically attack routine methods. Topics include independence and dependence, probability laws and random variables. Over 500 exercises, an appendix of useful tables and answers to odd-numbered questions are also included.
More details
Series
Edition
Wiley Classics Lib edition
Language
English
Place of publication
United States
Publishing group
John Wiley & Sons Inc
Target group
College/higher education
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 229 mm
Width: 152 mm
Thickness: 28 mm
Weight
779 gr
ISBN-13
978-0-471-57278-7 (9780471572787)
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
Emanuel Parzen
Modern Probability Theory and Its Applications
Book
12/1960
Wiley
€62.08
Article exhausted; check different version
Person
Emanuel Parzen was an American statistician. He worked and published on signal detection theory and time series analysis, where he pioneered the use of kernel density estimation. Parzen was the recipient of the 1994 Samuel S. Wilks Memorial Medal of the American Statistical Association.
Content
Probability Theory as the Study of Mathematical Models of RandomPhenomena.
Basic Probability Theory.
Independence and Dependence.
Numerical-Valued Random Phenomena.
Mean and Variance of a Probability Law.
Normal, Poisson, and Related Probability Laws.
Random Variables.
Expectation of a Random Variable.
Sums of Independent Random Variables.
Sequences of Random Variables.
Tables.
Answers to Odd-Numbered Exercises.
Index.
Basic Probability Theory.
Independence and Dependence.
Numerical-Valued Random Phenomena.
Mean and Variance of a Probability Law.
Normal, Poisson, and Related Probability Laws.
Random Variables.
Expectation of a Random Variable.
Sums of Independent Random Variables.
Sequences of Random Variables.
Tables.
Answers to Odd-Numbered Exercises.
Index.