## Description

**Statistics for Engineers and Scientists 5th Edition by William Navidi, ISBN-13: 978-1259717604**

[PDF eBook eTextbook]

- Publisher: McGraw Hill; 5th edition (January 25, 2019)
- Language: English
- 944 pages
- ISBN-10: 1259717607
- ISBN-13: 978-1259717604

* Statistics for Engineers and Scientists *stands out for its crystal 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:**

1) Sampling and Descriptive Statistics

2) Probability

3) Propagation of Error

4) Commonly Used Distributions

5) Confidence Intervals

6) Hypothesis Testing

7) Correlation and Simple Linear Regression

8) Multiple Regression

9) Factorial Experiments

10) Statistical Quality Control

Appendix A – Tables

Appendix B – Partial Derivatives

Appendix C – Bibliography

Answers to Odd-Numbered Exercises

Index

* William Navidi *received a B.A. in mathematics from New College, an M.A in

*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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