PDF Ebook Principles of Statistics for Engineers and Scientists
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Principles of Statistics for Engineers and Scientists
PDF Ebook Principles of Statistics for Engineers and Scientists
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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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Product details
Hardcover: 608 pages
Publisher: McGraw-Hill Education; 1 edition (January 26, 2009)
Language: English
ISBN-10: 0077289315
ISBN-13: 978-0077289317
Product Dimensions:
7.8 x 1.1 x 9.4 inches
Shipping Weight: 2.4 pounds (View shipping rates and policies)
Average Customer Review:
4.2 out of 5 stars
80 customer reviews
Amazon Best Sellers Rank:
#138,951 in Books (See Top 100 in Books)
The book explains concepts fairly well, and has decent example problems. However, I have an issue with it especially because it is a statistics book, where there are very minor equation shifts for very similar types of problems--it would be really nice if the book included a sort of equation sheet at the end of each chapter, stating the type of problem that each equation is useful for. Like after the chapter on hypothesis tests (which really blend together), it would be great if there were something like "Two-tailed hypothesis test, large sample: this equation; Chi-squared hypothesis test: this equation," etc. It had little boxes where there were important equations, but a summary sheet would have been incredibly helpful.
My students, on the whole like statistics. I think the text plays a key part in this. The problems are realistic and not over repetitive. I use R as my programming language for the course, with no difficulty.
Awesome book. Great examples and easy to follow hw problems.
Reading though the text book isn't too horrible, the book generally makes sense. My two main vices with this book is that it is sometimes difficult to understand what a specific symbol represents or where they got the value for it. I also don't like how you have chapters 1-10, the tables, answers to odd # questions then the index. It makes the tables incredibly difficult to find (except for the ones on the front and back cover. I recommend putting tabs into your own copy so you can find the tables easier.
The textbook served the purpose well for my stats class that it was required for. The book is pretty well laid out and has good summary boxes after each section. The one thing I would warn is that the same professor that wrote this book also wrote "Principles of Statistics for Engineers and Scientists", which is not the same. If you are getting this as a required textbook for a course, make sure you are getting the right textbook!
This book was alright for learning engineering statistics, but it wasn't as easy to follow and 'dumbed down' as I hoped it would be. It was a very challenging class and I wish the text book had done a little better job of explaining.
This is a wonderful, clear book for an introduction to statistics. It has plenty of concrete examples and it's well paced and laid out. I've used it extensively for my Ph.D. research in space physics. One word of caution: there's not really any discussion about time-series data, so if you're dealing with dependent samples or an autoregressive process, this book will only get you half way there.
This book is clear and concise. It's also very easy to understand and follow. I would've given 5 stars, but there was a little tear in the back cover.
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