Design of Experiments: An Introduction Based on Linear Models

Author:   Max Morris (Iowa State University, Ames, USA) ,  Chris Chatfield ,  Bradley P. Carlin ,  Martin Abba Tanner
Publisher:   Taylor & Francis Inc
Volume:   v. 87
ISBN:  

9781584889236


Pages:   376
Publication Date:   27 July 2010
Format:   Hardback
Availability:   In Print   Availability explained
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Design of Experiments: An Introduction Based on Linear Models


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Author:   Max Morris (Iowa State University, Ames, USA) ,  Chris Chatfield ,  Bradley P. Carlin ,  Martin Abba Tanner
Publisher:   Taylor & Francis Inc
Imprint:   Chapman & Hall/CRC
Volume:   v. 87
Dimensions:   Width: 15.60cm , Height: 2.40cm , Length: 23.40cm
Weight:   0.680kg
ISBN:  

9781584889236


ISBN 10:   1584889233
Pages:   376
Publication Date:   27 July 2010
Audience:   College/higher education ,  Undergraduate
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Reviews

It is truly my pleasure to read this book ! after reading this book, I benefitted by gaining insights into the modeling aspect of experimental design, and consequentially it helps me appreciate the idea of statistical efficiency behind each design and understand the tools used in data analysis. ! an excellent reference book that I would recommend to anyone who is serious about learning the nuts and bolts of experimental design and data analysis techniques. --Rong Pan, Journal of Quality Technology, Vol. 43, No. 3, July 2011


<p>It is truly my pleasure to read this book after reading this book, I benefitted by gaining insights into the modeling aspect of experimental design, and consequentially it helps me appreciate the idea of statistical efficiency behind each design and understand the tools used in data analysis. an excellent reference book that I would recommend to anyone who is serious about learning the nuts and bolts of experimental design and data analysis techniques.<br> Rong Pan, Journal of Quality Technology, Vol. 43, No. 3, July 2011


A distinctive feature of this excellent book is that it actually focuses on how to design an experiment. ... In all, an original and very useful book for students and instructors. -Stat Papers (2014) 55:1225-1226 the author has succeeded in striking a balance between the choice of topics and depth in discussion for teaching a course. The book is written with a refreshing style and succeeds in conveying the concepts to a reader. The treatment of the subject matter is thorough and the theory is clearly illustrated along with worked examples. Other books are available on similar topics but this book has the advantage that the chapters start with the classical non-matrix-theory approach to introduce the linear model and then converts it into a matrix theory-based linear model. This helps a reader, particularly a beginner, in clearly understanding the transition from a non-matrix approach to a matrix approach and to apply the results of matrix theory over linear models further. -Shalabh, Journal of the Royal Statistical Society, Series A, 2012 Overall, this is a book that is easy to like, with good definitions of designs, few typographical errors, and consistent, straightforward explications of the models ... I can picture a lot of students using a text aimed at a broad market design course but who need to understand more about what is going on behind the curtain. Morris' text also fills that gap very well. -Gary W. Oehlert, Biometrics, May 2012 It is truly my pleasure to read this book ... after reading this book, I benefitted by gaining insights into the modeling aspect of experimental design, and consequentially it helps me appreciate the idea of statistical efficiency behind each design and understand the tools used in data analysis. ... an excellent reference book that I would recommend to anyone who is serious about learning the nuts and bolts of experimental design and data analysis techniques. -Rong Pan, Journal of Quality Technology, Vol. 43, No. 3, July 2011


Author Information

Max D. Morris is a professor in the Department of Statistics and the Department of Industrial and Manufacturing Systems Engineering at Iowa State University. A fellow of the American Statistical Association, Dr. Morris is a recipient of the National Institute of Statistical Sciences Sacks Award for Cross-Disciplinary Research and the American Society for Quality Wilcoxon Prize.

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