(DOWNLOAD) "Design and Analysis of Experiments, Volume 3" by Klaus Hinkelmann " eBook PDF Kindle ePub Free
eBook details
- Title: Design and Analysis of Experiments, Volume 3
- Author : Klaus Hinkelmann
- Release Date : January 28, 2011
- Genre: Mathematics,Books,Science & Nature,
- Pages : * pages
- Size : 16120 KB
Description
Provides timely applications, modifications, and extensions of experimental designs for a variety of disciplines
Design and Analysis of Experiments, Volume 3: Special Designs and Applications continues building upon the philosophical foundations of experimental design by providing important, modern applications of experimental design to the many fields that utilize them. The book also presents optimal and efficient designs for practice and covers key topics in current statistical research.
Featuring contributions from leading researchers and academics, the book demonstrates how the presented concepts are used across various fields from genetics and medicinal and pharmaceutical research to manufacturing, engineering, and national security. Each chapter includes an introduction followed by the historical background as well as in-depth procedures that aid in the construction and analysis of the discussed designs. Topical coverage includes:
Genetic cross experiments, microarray experiments, and variety trials
Clinical trials, group-sequential designs, and adaptive designs
Fractional factorial and search, choice, and optimal designs for generalized linear models
Computer experiments with applications to homeland security
Robust parameter designs and split-plot type response surface designs
Analysis of directional data experiments
Throughout the book, illustrative and numerical examples utilize SAS®, JMP®, and R software programs to demonstrate the discussed techniques. Related data sets and software applications are available on the book's related FTP site.
Design and Analysis of Experiments, Volume 3 is an ideal textbook for graduate courses in experimental design and also serves as a practical, hands-on reference for statisticians and researchers across a wide array of subject areas, including biological sciences, engineering, medicine, and business.