Introduction to Probability, 2nd Rev edition

Introductory textbook for undergraduates, develops key ideas in probability and describes a variety of applications and of nonintuitive examples.

**Tag(s):**
Mathematics

**Publication date**: 01 Jul 1997

**ISBN-10**:
0821807498

**ISBN-13**:
9780821807491

**Paperback**:
520 pages

**Views**: 29,583

**Type**: Textbook

**Publisher**:
American Mathematical Society

**License**:
GNU Free Documentation License

**Post time**: 11 Jun 2005 07:10:16

Introduction to Probability, 2nd Rev edition

Introductory textbook for undergraduates, develops key ideas in probability and describes a variety of applications and of nonintuitive examples.

Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.3 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. A copy of the license is included in the section entitled "GNU Free Documentation License".

Click**here** to read the full license.

Click

From the Book Description:

This text is designed for an introductory probability course at the university level for sophomores, juniors, and seniors in mathematics, physical and social sciences, engineering, and computer science. It presents a thorough treatment of ideas and techniques necessary for a firm understanding of the subject. The text is also recommended for use in discrete probability courses.

The material is organized so that the discrete and continuous probability discussions are presented in a separate, but parallel, manner. This organization does not emphasize an overly rigorous or formal view of probabililty and therefore offers some strong pedagogical value. Hence, the discrete discussions can sometimes serve to motivate the more abstract continuous probability discussions.

This text is designed for an introductory probability course at the university level for sophomores, juniors, and seniors in mathematics, physical and social sciences, engineering, and computer science. It presents a thorough treatment of ideas and techniques necessary for a firm understanding of the subject. The text is also recommended for use in discrete probability courses.

The material is organized so that the discrete and continuous probability discussions are presented in a separate, but parallel, manner. This organization does not emphasize an overly rigorous or formal view of probabililty and therefore offers some strong pedagogical value. Hence, the discrete discussions can sometimes serve to motivate the more abstract continuous probability discussions.

Tweet

About The Author(s)

Charles M. Grinstead is a Professor at Department of Mathematics and Statistics, Swarthmore College.

Charles M. Grinstead is a Professor at Department of Mathematics and Statistics, Swarthmore College.

J. Laurie Snell received his PhD in mathematics in 1951 from the University of Illinois under the direction of Professor J. L. Doob. From 1951 to 1954 he was a Fine Instructor at Princeton. He then taught mathematics at Dartmouth College from 1954 to 1996. While at Dartmouth he developed, with Professors Kemeny and Thompson, the Finite Mathematics course and wrote with them the first Finite Mathematics book.

Book Categories

Computer Science
Introduction to Computer Science
Introduction to Computer Programming
Algorithms and Data Structures
Artificial Intelligence
Computer Vision
Machine Learning
Neural Networks
Game Development and Multimedia
Data Communication and Networks
Coding Theory
Computer Security
Information Security
Cryptography
Information Theory
Computer Organization and Architecture
Operating Systems
Image Processing
Parallel Computing
Concurrent Programming
Relational Database
Document-oriented Database
Data Mining
Big Data
Data Science
Digital Libraries
Compiler Design and Construction
Functional Programming
Logic Programming
Object Oriented Programming
Formal Methods
Software Engineering
Agile Software Development
Information Systems
Geographic Information System (GIS)

Mathematics
Mathematics
Algebra
Abstract Algebra
Linear Algebra
Number Theory
Numerical Methods
Precalculus
Calculus
Differential Equations
Category Theory
Proofs
Discrete Mathematics
Theory of Computation
Graph Theory
Real Analysis
Complex Analysis
Probability
Statistics
Game Theory
Queueing Theory
Operations Research
Computer Aided Mathematics

Supporting Fields
Web Design and Development
Mobile App Design and Development
System Administration
Cloud Computing
Electric Circuits
Embedded System
Signal Processing
Integration and Automation
Network Science
Project Management

Operating System
Programming/Scripting
Ada
Assembly
C / C++
Common Lisp
Forth
Java
JavaScript
Lua
Microsoft .NET
Rexx
Perl
PHP
Python
R
Rebol
Ruby
Scheme
Tcl/Tk

Miscellaneous
Sponsors