Customer Reviews

Statistical Methods for Engineers

5 star:		(2)
4 star:		(0)
3 star:		(0)
2 star:		(0)
1 star:		(6)

 

 

I must reiterate everything in Jamie Davey's review, and add a few of my own comments. I've had to teach from this book four times now, and I grow more irate with it every time. There is absolutely no diversity in the types of homework exercises it has. Within every section, every single problem takes the exact same form, only different words and numbers describing the situation. I've resorted to referring my class to other textbooks and taking a large number of examples and homework problems from this book's competitors. To add insult to injury, the solutions manual (both the instructor's CD and the solution in the back of the text) are replete with errors, which has caused a countless number of headaches. The only good thing I can think about this book is it is relatively thin, reducing the number of trees sacrificed to make this product.

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,

You will not learn what you need to know from this text. It is terribly written and does not give clear definitions or examples. Get something else, especially if you have to use this for a class. You will be lost without an exceptional instructor.

This textbook is hands down the worst book I have ever had the displeasure of using, and I have had some other bad ones too. This book is laid out in a terrible order and the examples are completely WORTHLESS!!!! You will be depending completely on your proffessor for any amount of learning you do in a course with this book. This book is so bad that it will litteraly have the exact same problem copyied and pasted 4-5 times at the end of each section with only slight alterations or different numbers.

I am not making this up either, one of the equations in this book is sigma = sqrt(sigma^2) ?!?!?!? I'm glad I have this book to teach me that.....

If you do not need this book for a course, then stay away from it at all costs!!!!!

I am a student who took at class which used this book. I am a person to tends to learn best out of the book and I have to say this book was terrible. A lot of the examples skipped over very important details. To me if it is something a student needs to show when showing working a homework problem then the book needs to show that as well in the examples.

I'm not a bit surprised by the overwhelming negative reviews of his book. I had a very unfortunate experience of taking a course from him some years back and, quite frankly, he's a pompous, arrogant, presumptuous jerk (he looks it, too, being a fatty with a curly hair, wearing eyeglasses and shabbily dressed frequently). Worse, he turned out to be a bigot, also (but, I'll just leave it at that). Anyway, he fails miserably as a professor and a textbook author, especially for most undergraduates who need all the help they can get to understand and learn the challenging, technical subject. It's too bad that people like him reinforce the negative stereotypes of techies as unattractive geeky jerks!

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".

the book was in very good condition when i got it. it was like someone bought it and then decided to sell it. and i got it only a day or two after i ordered it. Very good.