Introduction to Probability and Statistics for Engineers and Scientists

Introduction to Probability and Statistics for Engineers and Scientists

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Description

Suited for a first course in applied probability and statistics for engineering or science majors, this is a superior textbook. Introduction to Probability and Statistics for Engineers and Scientists, Second Edition, includes expanded coverage of quality control, and offers unique software that automates the computations required for exercises, as well as illustrating the main concepts of probability. The author emphasizes 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 sets are incorporated in a wide variety of exercises and examples throughout the book, and this emphasis on data motivates the probability coverage.
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Product details

  • Mixed media product | 578 pages
  • 196.1 x 241.8 x 33mm | 1,283.92g
  • Academic Press Inc
  • San Diego, United States
  • English
  • Revised
  • 2nd Revised edition
  • 0125984723
  • 9780125984720

Table of contents

Introduction to Statistics. Descriptive Statistics. Elements of Probability. Random Variables and Expectation. Special Random Variables. Distributions of Sampling Statistics. Parameter Estimation. Hypothesis Testing. Regression. Analysis of Variance. Goodness of Fit Tests and Categorical Data Analysis. Nonparametric Hypothesis Tests. Quality Control. Life Testing.
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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 California, Berkeley. He receivedhis Ph.D. in statistics at Stanford University in 1968 and has been at UC Berkeley ever since. He has published many technical articles and textbooks in the areas of statistics and applied probability. Professor Ross is the founding and contributing editor of the journal, Probability in the Engineering andInformational Sciences, published by Cambridge University Press. 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

41 ratings
3.41 out of 5 stars
5 27% (11)
4 27% (11)
3 20% (8)
2 15% (6)
1 12% (5)
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