What books provide an overview of engineering statistics? As an engineer, I'm interested in topics such as designing experiments that are statistically valid, quality control, process control, reliability, and cost control. I took a course in engineering statistics, but unfortunately neither the book nor the professor were that good. I did OK in the course, but I'm interested in learning more about these topics and how to apply them to engineering problems. I would prefer a general book that covered as many of these topics as possible - great depth is not needed.
I think that I can learn a lot about improving my abilities by looking at how all engineering disciplines use statistics, so I'm not looking for any particular engineering field.
Can the Statistical Analysis community recommend books that I can use to learn more about applying statistics to engineering problems?
 A: NIST/SEMATECH e-Handbook of Statistical Methods is a good start. Free and online:
http://www.itl.nist.gov/div898/handbook/
A: When I took the Engineering Statistics course I mentioned in the question, the assigned textbook wasn't very helpful. Instead, I used Probability and Statistics for Engineers and Scientists - Anthony Hayter to get through the course. It didn't cover everything in the same order and depth of the course, but it was sufficient to get me through the material and get a passing grade.
Topics covered include probability theory, random variables, discrete and continuous probability distributions, normal distributions, descriptive statistics, statistical estimation and sampling distributions, population means, discrete data analysis, ANOVA, linear regression, nonlinear regression, multifactor experimental design and analysis, nonparametric statistical analysis, quality control methods, and reliability analysis. Unfortunately, the course only covered the first 11 chapters and occasionally in more depth then this book went into.
A: The book Statistical Methods for Engineers - Geoffrey Vining is used in my university's Engineering Statistics course. However, I do not recommend this book. When I took the course, I ended up not being able to learn from the professor, so I was using this book to teach myself the material. It went along with the course in terms of content and depth, but I found the examples presented to be confusing and not as clear as they could have been. If you have a strong statistics background to begin with, it might be a suitable book, but this was the first statistics course that I had taken (and the only one required). There were no errors with the book - the examples and solutions were all correct.
If you are an engineer with a preexisting background in statistics, perhaps it might be worth it to visit your local library and check it out first before you buy it - it might work better for you than it did for me.
