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OverviewDesign and Analysis of Experiments with R presents a unified treatment of experimental designs and design concepts commonly used in practice. It connects the objectives of research to the type of experimental design required, describes the process of creating the design and collecting the data, shows how to perform the proper analysis of the data, and illustrates the interpretation of results. Drawing on his many years of working in the pharmaceutical, agricultural, industrial chemicals, and machinery industries, the author teaches students how to: Make an appropriate design choice based on the objectives of a research project Create a design and perform an experiment Interpret the results of computer data analysis The book emphasizes the connection among the experimental units, the way treatments are randomized to experimental units, and the proper error term for data analysis. R code is used to create and analyze all the example experiments. The code examples from the text are available for download on the author’s website, enabling students to duplicate all the designs and data analysis. Intended for a one-semester or two-quarter course on experimental design, this text covers classical ideas in experimental design as well as the latest research topics. It gives students practical guidance on using R to analyze experimental data. Full Product DetailsAuthor: John LawsonPublisher: Taylor & Francis Inc Imprint: Chapman & Hall/CRC Volume: 115 Dimensions: Width: 15.60cm , Height: 3.60cm , Length: 23.40cm Weight: 1.310kg ISBN: 9781439868133ISBN 10: 1439868131 Pages: 628 Publication Date: 17 December 2014 Audience: College/higher education , General/trade , Tertiary & Higher Education , General Format: Hardback Publisher's Status: Active Availability: In Print ![]() 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. Table of ContentsIntroduction. Completely Randomized Designs with One Factor. Factorial Designs. Randomized Block Designs. Designs to Study Variances. Fractional Factorial Designs. Incomplete and Confounded Block Designs. Split-Plot Designs. Crossover and Repeated Measures Designs. Response Surface Designs. Mixture Experiments. Robust Parameter Design Experiments. Experimental Strategies for Increasing Knowledge. Bibliography. Index.ReviewsThis is an excellent but demanding text. ... This book should be mandatory reading for anyone teaching a course in the statistical design of experiments. ... reading this text is likely to influence their course for the better. -MAA Reviews, March 2015 This is an excellent but demanding text. ... This book should be mandatory reading for anyone teaching a course in the statistical design of experiments. ... reading this text is likely to influence their course for the better. -MAA Reviews, March 2015 In my opinion, this is a very valuable book. It covers the topics that I judge should be in such a book including what might be called the standard designs and more ... it has become my go to text on experimental design. David E. Booth, Technometrics """This is an excellent but demanding text. … This book should be mandatory reading for anyone teaching a course in the statistical design of experiments. … reading this text is likely to influence their course for the better."" —MAA Reviews, March 2015 ""Thank you for writing your phenomenal book ""Design and Analysis of Experiments with R"". I'm teaching a new course this spring on experimental design and reinforcement learning. The students are graduate bioengineers, so I was having difficulty finding a text that blends theory, practice, and computation. Your book excels at all three. The first chapter I read clarified several topics and improved both my teaching and research. After testing a dozen DOE and RSM books, yours is the clear winner. I understand the enormous time that goes into a well-constructed textbook. I hope this message conveys my deep appreciation for your effort."" —Paul Jensen, Ph.D., Assistant Professor , Department of Bioengineering and Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign ""This is an excellent but demanding text. … This book should be mandatory reading for anyone teaching a course in the statistical design of experiments. … reading this text is likely to influence their course for the better."" —MAA Reviews, March 2015 ""In my opinion, this is a very valuable book. It covers the topics that I judge should be in such a book including what might be called the standard designs and more … it has become my go to text on experimental design."" David E. Booth, Technometrics" Author InformationJohn Lawson is a professor in the Department of Statistics at Brigham Young University. Tab Content 6Author Website:Countries AvailableAll regions |