Statistical Methods for Engineers

Rating:
Summary: Disappointed on many levels
Review: The book clearly fails to converse any information to the reader. Further, it also fails to relate topics from one chapter to another. I would not recommend this text to anyone who has basic, or even general, understanding of statistical methods. Please allow me to explain.

I am a student in engineering at the University of Ottawa. The class has been using the text for this semester and several previous semesters. To be quite blunt, the class averages have been well below satisfactory. I think the general lesson students have learned from this course is how and when a "bell" curve is implemented during course grading.

More Importantly, the text clearly fails to relate one idea to another. For example, in chapter two, the text introduces different data displays. The author fails to identify how these different displays are related, what is unique about each specific data display, and when to use a specific display. More over, in chapter three, Modeling Random Behavior, the author begins with an introduction to probability. He then introduces random variables but fails to clearly define and explain the different types of random variables. Next, the normal distribution is discussed. The author again fails to make the relationship between the normal distribution and random variables. Overall, the text poorly relates topics to one and other.

Additionally, problem examples are too short and lack clarity. Throughout the text, many practical examples are compiled into case studies. The problem is clearly identified, however, the solution is short, poorly justified, and not well explained. In general, it becomes very frustrating for a student attempting practice questions at the end of each section. Obviously, if the author successfully communicated the idea to the reader, the question would be logical and easy. The terminology "for engineers" used in the title of the text implies, in my opinion, that the ideas in the text are logically explained and clearly defined. Unfortunately, short examples that lack clarity prevent the reader from understanding the material logically.

In conclusion, if you must purchase this text, I would recommend a used copy. It's not worth the paper its printed on. The text fails to relate ideas together and does not have any detailed examples. Clearly, reading this book is about as enlightening as watching toilette flush.

Your in continuing disappointment,

Rating:
Summary: Excellent introductory text
Review: This book is quite readable, and provided me a good basis for further study. As I am in industry, I read through the examples as if they were part of the normal text, and skipped all the exercises at the end of each chapter. The book assumes the reader has the level and comfort with math that most engineers have, vs. biology focused people, eg it doesn't make excuses when it takes the derivative of something to show that least squares is optimal. The examples are also drawn from engineering, eg manufacturing tolerances rather than fertilizer yield. It has a high ratio of text to equations, helpful for gaining an intuitive understanding of what's going on.

For a gentler introduction to stats, I recommend Phillip's "How to Think About Statistics".