9780071242486-0071242481-Introduction to Probability and Statistics: Principles and Applications for Engineering and the Computing Sciences

Introduction to Probability and Statistics: Principles and Applications for Engineering and the Computing Sciences

ISBN-13: 9780071242486
ISBN-10: 0071242481
Edition: International Edition
Author: Arnold, MILTON
Publication date: 2002
Publisher: Mcgraw Hill Higher Education
Format: Paperback 832 pages
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Book details

ISBN-13: 9780071242486
ISBN-10: 0071242481
Edition: International Edition
Author: Arnold, MILTON
Publication date: 2002
Publisher: Mcgraw Hill Higher Education
Format: Paperback 832 pages

Summary

Introduction to Probability and Statistics: Principles and Applications for Engineering and the Computing Sciences (ISBN-13: 9780071242486 and ISBN-10: 0071242481), written by authors Arnold, MILTON, was published by Mcgraw Hill Higher Education in 2002. With an overall rating of 4.2 stars, it's a notable title among other Applied (Mathematics) books. You can easily purchase or rent Introduction to Probability and Statistics: Principles and Applications for Engineering and the Computing Sciences (Paperback, Used) from BooksRun, along with many other new and used Applied books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

This well-respected text is designed for the first course in probability and statistics taken by students majoring in Engineering and the Computing Sciences. The prerequisite is one year of calculus. The text offers a balanced presentation of applications and theory. The authors take care to develop the theoretical foundations for the statistical methods presented at a level that is accessible to students with only a calculus background. They explore the practical implications of the formal results to problem-solving so students gain an understanding of the logic behind the techniques as well as practice in using them. The examples, exercises, and applications were chosen specifically for students in engineering and computer science and include opportunities for real data analysis.

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