The eighth edition of this best selling text continues to help senior and graduate students in engineering, business, and statistics-as well as working practitioners-to design and analyze experiments for improving the quality, efficiency and performance of working systems. The eighth edition of Design and Analysis of Experiments maintains its comprehensive coverage by new examples, exercises, and problems (including in the areas of biochemistry and biotechnology); new topics and problems in the area of response surface; new topics in nested and split-plot design; and the residual maximum likelihood method is now emphasized throughout the book. Continuing to place a strong focus on the use of the computer, this edition includes software examples taken from the four most dominant programs in the Design-Expert, Minitab, JMP, and SAS.
This is a very straight-forward textbook with the help of an instructor's guidance. The very beginning, aka Chapters 1 and 2, are review from the very basics of statistics. It is after these that you do encounter different "types" of equations and ways to create models when it comes to actual real-life situations. In this case, these are dealing with small situations. You can compute these by hand, if you want, but when it comes to that of larger samples sizes, that's when you want to take the advice of using technology.
Again, a different kind of statistics, but very direct.
I think that this text is one of the best to approach design of experiment topic. Every chapter is described quantitatively, with a lot of real examples. The weak part of the text, is represented by regression chapter, described in a too BOS way, with few quantitative demostrations.
This book is very detailed and very readable. Great coverage of Design of Experiments and all things related. Accompanied the graduate course I took with the author very well!