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Principles of Statistics for Engineers and Scientists
Principles of Statistics for Engineers and Scientists

Principles of Statistics for Engineers and Scientists, 2nd Edition

ISBN10: 1260257819 | ISBN13: 9781260257816
By William Navidi
© 2021

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* The estimated amount of time this product will be on the market is based on a number of factors, including faculty input to instructional design and the prior revision cycle and updates to academic research-which typically results in a revision cycle ranging from every two to four years for this product. Pricing subject to change at any time.

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Available for the first time in McGraw-Hill's Connect! Principles of Statistics for Engineers and Scientists emphasizes statistical methods and how they can be applied to problems in science and engineering. The book contains many examples that feature real, contemporary data sets, both to motivate students and to show connections to industry and scientific research. Because statistical analyses are done on computers, the book contains exercises and examples that involve interpreting, as well as generating, computer output. This book may be used effectively with any software package.

1 Summarizing Univariate Data

2 Summarizing Bivariate Data

3 Probability

4 Commonly Used Distributions

5 Point and Interval Estimation for a Single Sample

6 Hypothesis Tests for a Single Sample

7 Inferences for Two Samples

8 Inference in Linear Models

9 Factorial Experiments

10 Statistical Quality Control

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About the Author

William Navidi

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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