P1188
Statistics for Experimenters: Design, Innovation, and Discovery, 2nd Edition
George E. P. Box, J. Stuart Hunter, William G. Hunter
656 pages. ISBN 0-471-71813-0. Hardcover. 2005
$145.00

Rewritten and updated, this new edition of Statistics for Experimenters adopts the same approaches as the landmark First Edition by teaching with examples, readily understood graphics, and the appropriate use of computers. Catalyzing innovation, problem solving, and discovery, the Second Edition provides experimenters with the scientific and statistical tools needed to maximize the knowledge gained from research data, illustrating how these tools may best be utilized during all stages of the investigative process. The authors’ practical approach starts with a problem that needs to be solved and then examines the appropriate statistical methods of design and analysis.

Providing even greater accessibility for its users, the Second Edition is thoroughly revised and updated to reflect the changes in techniques and technologies since the publication of the classic First Edition.

Among the new topics included are:

Graphical Analysis of Variance

Computer Analysis of Complex Designs

Simplification by transformation

Hands-on experimentation using Response Service Methods

Further development of robust product and process design using split plot arrangements and minimization of error transmission

Introduction to Process Control, Forecasting and Time Series

Illustrations demonstrating how multi-response problems can be solved using the concepts of active and inert factor spaces and canonical spaces

Bayesian approaches to model selection and sequential experimentation

An appendix featuring Quaquaversal quotes from a variety of sources including noted statisticians and scientists to famous philosophers is provided to illustrate key concepts and enliven the learning process.

All the computations in the Second Edition can be done utilizing the statistical language R. Functions for disp

Contents:

• 1. Catalizing the Generation of Knowledge.
  
• 2. Basics: Probability, Parameters and Statistics.
  
• 3. Comparing Two Entities: Relevant Reference Distributions, Tests and Confidence Intervals.
  
• 4. Comparing a Number of Entities: Randomized Blocks and Latin Squares.
  
• 5. Factorial Designs at Two Levels: Advantages of Experimental Design.
  
• 6. Fraction Factorial Designs: Economy in Experimentation.
  
• 7. Other Fractionals, Analysis and Choosing Follow-up Runs.
  
• 8. Factorial Designs and Data Transformation.
  
• 9. Multiple Sources of Variation: Split Plot Designs, Variance Components and Error Transmission.
  
• 10. Least Squares and Why You Need to Design Experiments.
  
• 11. Modelling Relationships, Sequential Assembly: Basics for Response Surface Methods.
  
• 12. Some Applications of Response Surface Methods.
  
• 13. Designing Robust Products: An Introduction.
  
• 14. Process Control, Forecasting and Times Series: An Introduction.
  
• 15. Evolutionary Process Operation.
  
• Appendices.
  
• Index.