A valuable guide to conducting experiments and analyzing data across a wide range of applications
Experimental design is an important component of the scientific method. This book provides guidance on planning efficient investigations. It compiles designs for a wide range of experimental situations not previously found in accessible form. Focusing on applications in the physical, engineering, biological, and social sciences, Planning, Construction, and Statistical Analysis of Comparative Experiments is a valuable guide to designing experiments and correctly analyzing and interpreting the results. The authors draw on their years of experience in the classroom and as statistical consultants to research programs on campus, in government, and in industry. The object is always to strike the right balance between mathematical necessities and practical constraints.
Serving both as a textbook for students of intermediate statistics and a hands-on reference for active researchers, the text includes:
A wide range of applications, including agricultural sciences, animal and biomedical sciences, and industrial engineering studies
General formulas for estimation and hypothesis testing, presented in a unified and simplified manner
Guidelines for evaluating the power and efficiency of designs that are not perfectly balanced
New developments in the design of fractional factorials with non-prime numbers of levels in mixed-level fractional factorials
Detailed coverage on the construction of plans and the relationship among categories of designs
Thorough coverage of balanced, lattice, cyclic, and alpha designs
Strategies for sequences of fractional factorials
Data sets and SAS® code on a companion web site
An ideal handbook for the investigator planning a research program, the text comes complete with detailed plans of experiments and alternative approaches for added flexibility.
Planning, Construction, and Statistical Analysis of Comparative Experiments
RRP:
$447.00
Description
A valuable guide to conducting experiments and analyzing data across a wide range of applications
Experimental design is an important component of the scientific method. This book provides guidance on planning efficient investigations. It compiles designs for a wide range of experimental situations not previously found in accessible form. Focusing on applications in the physical, engineering, biological, and social sciences, Planning, Construction, and Statistical Analysis of Comparative Experiments is a valuable guide to designing experiments and correctly analyzing and interpreting the results. The authors draw on their years of experience in the classroom and as statistical consultants to research programs on campus, in government, and in industry. The object is always to strike the right balance between mathematical necessities and practical constraints.
Serving both as a textbook for students of intermediate statistics and a hands-on reference for active researchers, the text includes:
A wide range of applications, including agricultural sciences, animal and biomedical sciences, and industrial engineering studies
General formulas for estimation and hypothesis testing, presented in a unified and simplified manner
Guidelines for evaluating the power and efficiency of designs that are not perfectly balanced
New developments in the design of fractional factorials with non-prime numbers of levels in mixed-level fractional factorials
Detailed coverage on the construction of plans and the relationship among categories of designs
Thorough coverage of balanced, lattice, cyclic, and alpha designs
Strategies for sequences of fractional factorials
Data sets and SAS® code on a companion web site
An ideal handbook for the investigator planning a research program, the text comes complete with detailed plans of experiments and alternative approaches for added flexibility.
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This title is part of UC Press's Voices Revived program, which commemorates University of California Press’s mission to seek out and cultivate the brightest minds and give them voice, reach, and...
Emphasizes the strategy of experimentation, data analysis, and the interpretation of experimental results. Features numerous examples using actual engineering and scientific studies.
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