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Planning, Construction, and Statistical Analysis of Comparative Experiments - Hardcover

 
9780471213956: Planning, Construction, and Statistical Analysis of Comparative Experiments

Synopsis

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.

"synopsis" may belong to another edition of this title.

About the Author

FRANCIS G. GIESBRECHT, PhD, is Professor Emeritus in the Department of Statistics at North Carolina State University in Raleigh, North Carolina. He earned his PhD in Statistics from the Iowa State University.

MARCIA L. GUMPERTZ, PhD, is a professor in the Department of Statistics at North Carolina State University where she also received her PhD in Statistics.

Review

"...an excellent reference for statisticians and practitioners who would like to gain broad exposure to the tools available for studying relationships between qualitative and quantitative factors..." (Journal of the American Statistical Association, June 2005)

“The level of detail is higher than in most other books on similar topics and therefore makes this one a useful reference tool.” (Short Book Reviews, Vol.25, No.1, April 2005)

"I will instruct statistician reporting to me to get a copy of the book, and will keep the review copy readily available on my shelf..." (Technometrics, February 2005)

"There is a moderate amount of material that is not in other design books...in addition to some tricks of the trade that appear to be new...practitioners...will find the book useful." (Journal of Quality Technology, October 2004)

"...an excellent resource handbook for researchers and statisticians, providing them with the tools necessary to construct better experiments and plan more efficient investigations.” (CHOICE, October 2004)

"About this title" may belong to another edition of this title.

  • PublisherWiley-Interscience
  • Publication date2004
  • ISBN 10 0471213950
  • ISBN 13 9780471213956
  • BindingHardcover
  • LanguageEnglish
  • Edition number1
  • Number of pages720

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Hardcover. Condition: new. Hardcover. 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 studiesGeneral formulas for estimation and hypothesis testing, presented in a unified and simplified mannerGuidelines for evaluating the power and efficiency of designs that are not perfectly balancedNew developments in the design of fractional factorials with non-prime numbers of levels in mixed-level fractional factorialsDetailed coverage on the construction of plans and the relationship among categories of designsThorough coverage of balanced, lattice, cyclic, and alpha designsStrategies for sequences of fractional factorialsData 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. The outgrowth of more than 40 years of experience teaching and consulting with students and active researchers in many disciplines, this is a useful guide for both students and active researchers to experimental design. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780471213956

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