نام کتاب
Statistics for Engineers and Scientists

William Navidi

Paperback961 Pages
PublisherMcGraw Hill
Edition6
LanguageEnglish
Year2024
ISBN9781265875855
663
A5039
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#Statistics

#Engineers

#Scientists

#Data_analysis

توضیحات


Statistics for Engineers and Scientists stands out for its clear presentation of applied statistics. The book takes a practical approach to methods of statistical modeling and data analysis that are most often used in scientific work. This edition features a unique approach highlighted by an engaging writing style that explains difficult concepts clearly, along with the use of contemporary real world data sets, to help motivate students and show direct connections to industry and research. While focusing on practical applications of statistics, the text makes extensive use of examples to motivate fundamental concepts and to develop intuition.


Table of Contents

Chapter 1 Sampling and Descriptive Statistics

Chapter 2 Probability

Chapter 3 Propagation of Error

Chapter 4 Commonly Used Distributions

Chapter 5 Confidence Intervals

Chapter 6 Hypothesis Testing

Chapter 7 Correlation and Simple Linear Regression

Chapter 8 Multiple Regression

Chapter 9 Factorial Experiments

Chapter 10 Statistical Quality Control

Appendix A: Tables

Appendix B: Partial Derivatives

Appendix C: Data Sets

Appendix D: References

Answers to Selected Exercises


About the Author

William Navidi received a B.A. in mathematics from New College, an M.A in mathematics from Michigan State University, and a Ph.D. in statistics from the University of California at Berkeley. Dr. Navidi is a professor of applied mathematics and statistics at the Colorado School of Mines in Golden, Colorado. He began his teaching career at the County College of Morris in Dover, New Jersey. He has taught mathematics and statistics at all levels, from developmental through the graduate level. Dr. Navidi has written two engineering statistics textbooks for McGraw-Hill and has authored more than 50 research papers, both in statistical theory and in a wide variety of applications, including computer networks, epidemiology, molecular biology, chemical engineering, and geophysics.

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