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, JMP, and MINITAB 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.
This volume covers the first full year of experimental design topics at the beginning graduate level. It attempts to present a well-balanced, down-to-earth, but complete coverage of the subject matter, with equal emphasis on both design and analysis. The mathematical rigor is strictly kept to a minimum.
