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This completely revised and updated second edition of the premier guide and reference for the
application of statistical methods as applied to experimental design adopts the same approaches as the
landmark first edition: It provides the tools needed to maximize the knowledge gained from research
data by teaching with examples, readily understood graphics, and the appropriate use of computers.
It explains how to employ this knowledge using a scientific and statistical outlook when
collecting, analyzing, and interpreting data. Recommended.
From the Preface: “...Under such banners as `Six Sigma,' management has realized the importance
of training its work forces in the arts of economic investigation. With this democratization of the
scientific method, many more people are being found with creative ability and unrealized aptitude
for problem solving and discovery...Also based on long experience, we believe the material in this
book provides appropriate training for scientists and engineers at universities whose needs have in the
past been frequently neglected...”
Target Audience: Individuals — including students and professionals in industry and commerce
— who must use statistical approaches to conduct an experiment, but who do not necessarily have
formal training in statistical analysis.
Table of Contents:
Catalyzing the Generation of Knowledge
Basics (Probability, Parameters, and Statistics)
Comparing Two Entities: Reference Distributions, Tests, and Confidence Intervals
Comparing a Number of Entities: Randomized Blocks, and Latin Squares
Factorial Design at Two Levels
Fractional Factorial Designs
Additional Fractionals and Analysis
Factorial Designs and Data Transformation
Multiple Sources of Variation
Least Squares and Why We Need Designed Experiments
Modeling, Geometry, and Experimental Design
Some Applications of Response Surface Methods
Designing Robust Products and Processes: An Introduction
Process Control, Forecasting, and Time Series: An Introduction
Evolutionary Process Operation
Appendices
Index
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