Principles of Statistics for Engineers and Scientists https://www.mheducation.com/cover-images/Jpeg_400-high/0077289315.jpeg 1 9780077289317 Principles of Statistics for Engineers and Scientists offers the same crystal clear presentation of applied statistics as Bill Navidi's Statistics for Engineers and Scientists text, in a manner especially designed for the needs of a one-semester course that focuses on applications. The text features a unique approach accentuated by an engaging writing style that explains difficult concepts clearly. By presenting ideas in the context of real-world data featured in plentiful examples, the book motivates students to understand fundamental concepts through practical examples found in industry and research.
Principles of Statistics for Engineers and Scientists

Principles of Statistics for Engineers and Scientists

1st Edition
By William Navidi
ISBN10: 0077289315
ISBN13: 9780077289317
Copyright: 2010
09780077289317

Purchase Options

Students, we’re committed to providing you with high-value course solutions backed by great service and a team that cares about your success. See tabs below to explore options and pricing. Don't forget, we accept financial aid and scholarship funds in the form of credit or debit cards.

Hardcopy

Receive via shipping:

  • Bound book containing the complete text
  • Full color
  • Hardcover or softcover

What are my shipping options?


ISBN10: 0077289315 | ISBN13: 9780077289317

Purchase

$246.33

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.

Program Details

1 Sampling and Descriptive Statistics

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

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.