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A Comprehensive Guide to Factorial Two-Level Experimentation [Hardcover]

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  • Category: Books (Mathematics)
  • Author:  Mee, Robert
  • Author:  Mee, Robert
  • ISBN-10:  0387891021
  • ISBN-10:  0387891021
  • ISBN-13:  9780387891026
  • ISBN-13:  9780387891026
  • Publisher:  Springer
  • Publisher:  Springer
  • Binding:  Hardcover
  • Binding:  Hardcover
  • Pub Date:  01-Mar-2009
  • Pub Date:  01-Mar-2009
  • SKU:  0387891021-11-SPRI
  • SKU:  0387891021-11-SPRI
  • Item ID: 100704283
  • List Price: $109.99
  • Seller: ShopSpell
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  • Delivery by: Dec 01 to Dec 03
  • Notes: Brand New Book. Order Now.

This book contains the most comprehensive coverage available anywhere for two-level factorial designs.

The re-analysis of 50 published examples serves as a how-to guide for analysis of the many types of full factorial and fractional factorial designs.

By focusing on two-level designs, this book is accessible to a wide audience of practitioners who use planned experiments.

With applications in virtually every quantitative field, the statistical design of experiments is a useful skill. Practitioners wanting to expand their repertoire will find this book a helpful guide, while examples from many fields give the book broad appeal.

Factorial designs enable researchers to experiment with many factors. The 50 published examples re-analyzed in this guide attest to the prolific use of two-level factorial designs. As a testimony to this universal applicability, the examples come from diverse fields: Analytical Chemistry, Animal Science, Automotive Manufacturing, Ceramics and Coatings, Chromatography, Electroplating, Food Technology, Injection Molding, Marketing, Microarray Processing, Modeling and Neural Networks, Organic Chemistry, Product Testing, Quality Improvement, Semiconductor Manufacturing, and Transportation.

Focusing on factorial experimentation with two-level factors makes this book unique, allowing the only comprehensive coverage of two-level design construction and analysis. Furthermore, since two-level factorial experiments are easily analyzed using multiple regression models, this focus on two-level designs makes the material understandable to a wide audience. This book is accessible to non-statisticians having a grasp of least squares estimation for multiple regression and exposure to analysis of variance.

This book contains a wealth of information, including recent results on the design of two-level factorials and various al1

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