Introduction to Probability and Statistics for Engineers and Scientists, 6th Edition

Introduction to Probability and Statistics for Engineers and Scientists, 6th Edition
PDF
  • eBook:
    Introduction to Probability and Statistics for Engineers and Scientists, 6th Edition
  • Author:
    Sheldon M. Ross
  • Edition:
    6 edition
  • Categories:
  • Data:
    November 15, 2020
  • ISBN:
    0128177462
  • ISBN-13:
    9780128177464
  • Language:
    English
  • Pages:
    704 pages
  • Format:
    PDF

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.

Content

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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