9781119717867-1119717868-Probability With Stem Applications

Probability With Stem Applications

ISBN-13: 9781119717867
ISBN-10: 1119717868
Edition: 3
Author: Jay L. Devore, Matthew A. Carlton
Publication date: 2016
Publisher: John Wiley & Sons Inc
Format: Paperback 563 pages
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Book details

ISBN-13: 9781119717867
ISBN-10: 1119717868
Edition: 3
Author: Jay L. Devore, Matthew A. Carlton
Publication date: 2016
Publisher: John Wiley & Sons Inc
Format: Paperback 563 pages

Summary

Probability With Stem Applications (ISBN-13: 9781119717867 and ISBN-10: 1119717868), written by authors Jay L. Devore, Matthew A. Carlton, was published by John Wiley & Sons Inc in 2016. With an overall rating of 4.4 stars, it's a notable title among other Industrial, Manufacturing & Operational Systems (Engineering) books. You can easily purchase or rent Probability With Stem Applications (Paperback) from BooksRun, along with many other new and used Industrial, Manufacturing & Operational Systems books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

Probability with STEM Applications, Third Edition, is an accessible and well-balanced introduction to post-calculus applied probability. Integrating foundational mathematical theory and the application of probability in the real world, this leading textbook engages students with unique problem scenarios and more than 1100 exercises of varying levels of difficulty. The text uses a hands-on, software-oriented approach to the subject of probability. MATLAB and R examples and exercises -- complemented by computer code that enables students to create their own simulations -- demonstrate the importance of software to solve problems that cannot be obtained analytically.

Revised and updated throughout, the textbook covers random variables and probability distributions, the basics of statistical inference, Markov chains, stochastic processes, signal processing, and more. This new edition is the perfect text for both year-long and single-semester mathematics and statistics courses, student engineers and scientists, and business and social science majors wanting to learn the quantitative aspects of their disciplines.

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