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Probability and Statistics for Engineers and Scientists: PNIE, 9/e


Probability and Statistics for Engineers and Scientists: PNIE, 9/e
Author(s)  Ronald E. Walpole, Keying Ye, Sharon L. Myers and Raymond H. Myers
ISBN  9789332519084
Imprint  Pearson Education
Copyright  2014
Pages  950
Binding  Paperback
List Price  Rs. 1190.00
  
 
 

This classic text provides a rigorous introduction to basic probability theory and statistical inference, with a unique balance between theory and methodology. Interesting, relevant applications use real data from actual studies, showing how the concepts and methods can be used to solve problems in the field. This revision focuses on improved clarity and deeper understanding.

  • About the Authors
  • Contents
  • Features
  • Downloadable Resources

• Ronald E. Walpole


• Raymond H. Myers, Virginia Polytechnic Institute


• Sharon L. Myers


• Keying E. Ye, Virginia Polytechnic Institute & State University


 

 

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. Sampling Distributions and More Graphical Tools


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


A. Statistical Tables and Proofs


B. Answers to Odd-Numbered Non-Review Exercises


 

 

• The balance between theory and applications offers mathematical support to enhance coverage when necessary, giving engineers and scientists the proper mathematical context for statistical tools and methods.


• Mathematical level: this text assumes one semester of differential and integral calculus as a prerequisite.


o Calculus is confined to elementary probability theory and probability distributions (Chapters 2—7).


o Matrix algebra is used modestly in coverage of linear regression material (Chapters 11—12).


o Linear algebra and the use of matrices are applied in Chapters 11—15, where treatment of linear regression and analysis of variance is covered.


• Compelling exercise sets challenge students to use the concepts to solve problems that occur in many real-life scientific and engineering situations. Many exercises contain real data from studies in the fields of biomedical, bioengineering, business, computing, etc.


o Real-life applications of the Poisson, binomial, and hypergeometric distributions generate student interest using topics such as flaws in manufactured copper wire, highway potholes, hospital patient traffic, airport luggage screening, and homeland security.


 

 
 
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