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CRC Press
Published: Tuesday, May 25, 2010 - 15:32
Emphasizes the connection between experimental units, the way treatments are randomized to experimental units, and the proper error term for an analysis of data
Uses SAS 9.2 throughout to illustrate the construction of experimental designs and data analysis
Provides uniform coverage on experimental designs and design concepts that are most commonly used in practice
Presents many applications from the pharmaceutical, agricultural, industrial chemicals, and machinery industries
Includes exercises at the end of every chapter
Offers all the SAS codes, for example on http://lawson.mooo.com/
Drawing on a variety of application areas, from pharmaceuticals to machinery, the book presents numerous examples of experiments and exercises that enable students to perform their own experiments.
Harnessing the capabilities of SAS 9.2, it includes examples of SAS data step programming and IML, along with procedures from SAS Stat, SAS QC, and SAS OR. The text also shows how to display experimental results graphically using SAS ods graphics.
The author emphasizes how the sample size, the assignment of experimental units to combinations of treatment factor levels (error control), and the selection of treatment factor combinations (treatment design) affect the resulting variance and bias of estimates as well as the validity of conclusions.
This textbook covers both classical ideas in experimental design and the latest research topics. It clearly discusses the objectives of a research project that lead to an appropriate design choice, the practical aspects of creating a design and performing experiments, and the interpretation of the results of computer data analysis.
Published May 4 by CRC Press, Design and analysis of Experiments with SAS is part of the Chapman & Hall/CRC Texts in Statistical Science series.
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
John Lawson, Ph.D., has taught at Brigham Young University (BYU) since 1986, most often in courses on reliability, advanced experimental design, and quality improvement for industry; he also advises quality science undergraduates. Lawson is the faculty advisor for the BYU Student Section of the American Society for Quality (ASQ). Quality Digest does not charge readers for its content. We believe that industry news is important for you to do your job, and Quality Digest supports businesses of all types. However, someone has to pay for this content. And that’s where advertising comes in. Most people consider ads a nuisance, but they do serve a useful function besides allowing media companies to stay afloat. They keep you aware of new products and services relevant to your industry. All ads in Quality Digest apply directly to products and services that most of our readers need. You won’t see automobile or health supplement ads. So please consider turning off your ad blocker for our site. Thanks, CRC Press is a premier global publisher of science, technology, and medical resources. It offers unique, trusted content by expert authors, spreading knowledge and promoting discovery worldwide. Its aim is to broaden thinking and advance understanding in the sciences, providing researchers, academics, professionals, and students with the tools they need to share ideas and realize their potential. CRC Press is a member of Taylor & Francis Group, an informa business.Book: Design and Analysis of Experiments with SAS
A practical guidance on the computer analysis of experimental data
(CRC Press: Boca Raton, FL) -- The new book, Design and Analysis of Experiments with SAS, is a culmination of author John Lawson’s many years of consulting and teaching. It provides practical guidance on the computer analysis of experimental data. The book connects the objectives of research to the type of experimental design required, describes the actual 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.
Features
Chapters
Response Surface Designs
Mixture Experiments
Robust Parameter Design Experiments
Experimental Strategies for Increasing Knowledge
Prior to his teaching career, Lawson worked in industry for 15 years as a senior biostatistician at Johnson & Johnson, the manager of Corporation Statistics Group, and the internal consultant for the FMC Corp. in Princeton, New Jersey. He continues to consult through the Center for Statistical Research, and for several corporations.
Lawson received his doctorate in statistics in 1984 at the Polytechnic Institute in New York. He received two master of science degrees in statistics, one at Rutgers University in 1978, and the other at Brigham Young University in 1971. His bachelor of science degree, which he received in 1969, was also in statistics.
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