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ISE Principles of Statistics for Engineers and Scientists

William Navidi

$159.95

Paperback

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English
McGraw-Hill Education
17 February 2020
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.

By:  
Imprint:   McGraw-Hill Education
Country of Publication:   United States
Edition:   2nd edition
Dimensions:   Height: 231mm,  Width: 185mm,  Spine: 23mm
Weight:   789g
ISBN:   9781260570731
ISBN 10:   1260570738
Pages:   626
Publication Date:  
Audience:   College/higher education ,  Primary
Format:   Paperback
Publisher's Status:   Active
1 Summarizing Univariate Data2 Summarizing Bivariate Data3 Probability4 Commonly Used Distributions5 Point and Interval Estimation for a Single Sample6 Hypothesis Tests for a Single Sample7 Inferences for Two Samples8 Inference in Linear Models9 Factorial Experiments10 Statistical Quality Control

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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