Probability and Statistics for Engineers and Scientists, 9 edition

Probability and Statistics for Engineers and Scientists, 9 edition
  • eBook:
    Probability and Statistics for Engineers and Scientists, 9 edition
  • Author:
    Ronald E. Walpole
  • Edition:
    9 edition
  • Categories:
  • Data:
    August 2016
  • ISBN:
  • ISBN-13:
  • Language:
  • Pages:
    812 pages
  • Format:

Book Description
Our emphasis in creating this edition is less on adding new material and more on providing clarity and deeper understanding. This objective was accomplished in part by including new end-of-chapter material that adds connective tissue between chapters. We affectionately call these comments at the end of the chapter “Pot Holes.” They are very useful to remind students of the big picture and how each chapter fits into that picture, and they aid the student in learning about limitations and pitfalls that may result if procedures are misused. A deeper understanding of real-world use of statistics is made available through class projects, which were added in several chapters. These projects provide the opportunity for students
alone, or in groups, to gather their own experimental data and draw inferences. In some cases, the work involves a problem whose solution will illustrate the meaning of a concept or provide an empirical understanding of an important statistical result. Some existing examples were expanded and new ones were introduced to create “case studies,” in which commentary is provided to give the student a clear understanding of a statistical concept in the context of a practical situation.


1. Introduction to Statistics and Data Analysis
2. Probability
3. Random Variables and Probability Distributions
4. Mathematical Expectation
5. Some Discrete Probability Distributions
6. Some Continuous Probability Distributions
7. Functions of Random Variables (Optional)
8. Fundamental Sampling Distributions and Data Descriptions
9. One- and Two-Sample Estimation Problems
10. One- and Two-Sample Tests of Hypotheses
11. Simple Linear Regression and Correlation
12. Multiple Linear Regression and Certain Nonlinear Regression Models
13. One-Factor Experiments: General
14. Factorial Experiments (Two or More Factors)
15. 2k Factorial Experiments and Fractions
16. Nonparametric Statistics
17. Statistical Quality Control
18. Bayesian Statistics

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