Modern Probability Theory and Its Applications/

By:

Parzen, Emanuel

Material type: Text

TextPublication details: New York: Wiley, [1960]Description: 464 p.:illSubject(s):

Probabilities

DDC classification:

519.1 PAR

LOC classification:

QA273 .P272 1960

Summary: This book is written as a textbook for a course in probability that can be adapted to the needs of students with diverse interests and backgrounds. The first six chapters constitute a one-quarter course in elementary probability theory. The material in the first eight chapters can be conveniently covered in thirty-nine class hours by students with a good working knowledge of calculus. Chapters nine and ten constitute an introduction to the limit theorems of probability theory and to the role of characteristic functions in probability theory. These chapters provide careful and rigorous derivations of the law of large numbers and the central limit theorem and contain many new proofs.

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Monograph & others	CBN HQ Library General Stacks	Non-fiction	519.1 PAR (Browse shelf(Opens below))	Available		31008100139415

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Previous	519.1 HUA Regression and econometric methods /	519.1 PAP Probability, Random Variables, and Stochastic Processes /	519.1 PAR Stochastic Processes /	519.1 PAR Modern Probability Theory and Its Applications/	519.2 BRE Probability and Stochastic Processes:	519.2 CLA Random Variables/	519.2 EST Estimating and Interpreting Probability Density Functions /	Next

Includes indexes: p. [459]-464.

This book is written as a textbook for a course in probability that can be adapted to the needs of students with diverse interests and backgrounds. The first six chapters constitute a one-quarter course in elementary probability theory. The material in the first eight chapters can be conveniently covered in thirty-nine class hours by students with a good working knowledge of calculus. Chapters nine and ten constitute an introduction to the limit theorems of probability theory and to the role of characteristic functions in probability theory. These chapters provide careful and rigorous derivations of the law of large numbers and the central limit theorem and contain many new proofs.

ne 23/03/2018

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