Introduction to Probability and Statistics for Engineers and Scientists

Introduction to Probability and Statistics for Engineers and Scientists

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Introduction to Probability and Statistics for Engineers and Scientists, Fifth Edition is a proven text reference that provides a superior introduction to applied probability and statistics for engineering or science majors. The book lays emphasis in the manner in which probability yields insight into statistical problems, ultimately resulting in an intuitive understanding of the statistical procedures most often used by practicing engineers and scientists.

Real data from actual studies across life science, engineering, computing and business are incorporated in a wide variety of exercises and examples throughout the text. These examples and exercises are combined with updated problem sets and applications to connect probability theory to everyday statistical problems and situations. The book also contains end of chapter review material that highlights key ideas as well as the risks associated with practical application of the material. Furthermore, there are new additions to proofs in the estimation section as well as new coverage of Pareto and lognormal distributions, prediction intervals, use of dummy variables in multiple regression models, and testing equality of multiple population distributions.

This text is intended for upper level undergraduate and graduate students taking a course in probability and statistics for science or engineering, and for scientists, engineers, and other professionals seeking a reference of foundational content and application to these fields.
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Product details

  • Hardback | 686 pages
  • 200.66 x 238.76 x 38.1mm | 1,700.96g
  • Academic Press Inc
  • San Diego, United States
  • English
  • 5th edition
  • Approx. 140 illustrations
  • 0123948118
  • 9780123948113
  • 532,227

Table of contents

1. Introduction to Statistics 2. Descriptive Statistics 3. Elements of Probability 4. Random Variables and Expectation 5. Special Random Variables 6. Distributions of Sampling Statistics 7. Parameter Estimation 8. Hypothesis Testing 9. Regression 10. Analysis of Variance 11. Goodness of Fit Tests and Categorical Data Analysis 12. non parametric HypothesisTests 13. Quality Control 14. LifeTesting 15. Simulation, Bootstrap Statistical Methods, and Permutation Tests
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Review Text

"...the book is intended for an introductory course, and assumes elementary calculus." -- Gazette of the Australian Mathematical Society
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Review quote

"...the book is intended for an introductory course, and assumes elementary calculus." --Gazette of the Australian Mathematical Society
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About Sheldon M. Ross

Sheldon M. Ross is a professor in the Department of Industrial Engineering and Operations Research at the University of Southern California. He received his Ph.D. in statistics at Stanford University in 1968. He has published many technical articles and textbooks in the areas of statistics and applied probability. Among his texts are A First Course in Probability, Introduction to Probability Models, Stochastic Processes, and Introductory Statistics. Professor Ross is the founding and continuing editor of the journal Probability in the Engineering and Informational Sciences. He is a Fellow of the Institute of Mathematical Statistics, and a recipient of the Humboldt US Senior Scientist Award.
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Rating details

42 ratings
3.45 out of 5 stars
5 29% (12)
4 26% (11)
3 19% (8)
2 14% (6)
1 12% (5)
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