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Introduction to Probability and Statistics for Engineers and Scientists

Introduction to Probability and Statistics for Engineers and Scientists

Authors
Publisher Elsevier Science Publishing Co Inc
Year 08/02/2021
Pages 704
Version hardback
Readership level College/higher education
Language English
ISBN 9780128243466
Categories Probability & statistics
$128.96 (with VAT)
573.30 PLN / €122.91 / £106.70
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Book description

Introduction to Probability and Statistics for Engineers and Scientists, Sixth Edition, uniquely emphasizes how probability informs statistical problems, thus helping readers develop an intuitive understanding of the statistical procedures commonly used by practicing engineers and scientists. Utilizing real data from actual studies across life science, engineering, computing and business, this useful introduction supports reader comprehension through a wide variety of exercises and examples. End-of-chapter reviews of materials highlight key ideas, also discussing the risks associated with the practical application of each material. In the new edition, coverage includes information on Big Data and the use of R.

This book is intended for upper level undergraduate and graduate students taking a probability and statistics course in engineering programs as well as those across the biological, physical and computer science departments. It is also appropriate for scientists, engineers and other professionals seeking a reference of foundational content and application to these fields.

Introduction to Probability and Statistics for Engineers and Scientists

Table of contents

CHAPTER 1 Introduction to statistics



CHAPTER 2 Descriptive statistics



CHAPTER 3 Elements of probability



CHAPTER 4 Random variables and expectation



CHAPTER 5 Special random variables



CHAPTER 6 Distributions of sampling statistics



CHAPTER 7 Parameter estimation



CHAPTER 8 Hypothesis testing



CHAPTER 9 Regression



CHAPTER 10 Analysis of variance



CHAPTER 11 Goodness of fit tests and categorical data analysis



CHAPTER 12 Nonparametric hypothesis tests



CHAPTER 13 Quality control



CHAPTER 14 Life testing



CHAPTER 15 Simulation, bootstrap statistical methods, and permutation tests



CHAPTER 16 Machine learning and big data

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