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A complete and well-balanced introduction to modern experimental design
Using current research and discussion of the topic along with clear applications, Modern Experimental Design highlights the guiding role of statistical principles in experimental design construction. This text can serve as both an applied introduction as well as a concise review of the essential types of experimental designs and their applications.
Topical coverage includes designs containing one or multiple factors, designs with at least one blocking factor, split-unit designs and their variations as well as supersaturated and Plackett-Burman designs. In addition, the text contains extensive treatment of:
_ Conditional effects analysis as a proposed general method of analysis
_ Multiresponse optimization
_ Space-filling designs, including Latin hypercube and uniform designs
_ Restricted regions of operability and debarred observations
_ Analysis of Means (ANOM) used to analyze data from various types of designs
_ The application of available software, including Design-Expert(r), JMP(r), and MINITAB(r)
This text provides thorough coverage of the topic while also introducing the reader to new approaches. Using a large number of references with detailed analyses of datasets, Modern Experimental Design works as a well-rounded learning tool for beginners as well as a valuable resource for practitioners.
Using current research and discussion of the topic along with clear applications, Modern Experimental Design highlights the guiding role of statistical principles in experimental design construction. This text can serve as both an applied introduction as well as a concise review of the essential types of experimental designs and their applications.
Topical coverage includes designs containing one or multiple factors, designs with at least one blocking factor, split-unit designs and their variations as well as supersaturated and Plackett-Burman designs. In addition, the text contains extensive treatment of:
_ Conditional effects analysis as a proposed general method of analysis
_ Multiresponse optimization
_ Space-filling designs, including Latin hypercube and uniform designs
_ Restricted regions of operability and debarred observations
_ Analysis of Means (ANOM) used to analyze data from various types of designs
_ The application of available software, including Design-Expert(r), JMP(r), and MINITAB(r)
This text provides thorough coverage of the topic while also introducing the reader to new approaches. Using a large number of references with detailed analyses of datasets, Modern Experimental Design works as a well-rounded learning tool for beginners as well as a valuable resource for practitioners.
"A good introduction to statistical design of experiments, covering a wide variety of topics in a well readable and structured way." (Statistical Papers 2008)
"It is definitely nice to have such a book in the library." (International Statistical Review, 2007)
"... this book will prove to be a boon for advances in experimental design." (Zentralblatt MATH, 2007)
"It is definitely nice to have such a book in the library." (International Statistical Review, 2007)
"... this book will prove to be a boon for advances in experimental design." (Zentralblatt MATH, 2007)