Elucidating a structure for experimentation that reduces excess expenditure of resources, this book explores the basic philosophy behind experimental design and the organizational aspects necessary to carry out both large- and small-scale endeavors. The author offers summaries of key concepts, end-of-chapter problems, and complete step-by-step examples for all methods and techniques covered. He integrates the robust design methodology introduced by Taguchi as a natural part of the design effort and establishes a criterion for measurement variables. The book presents the mathematical aspects of statistical experimental design in an intuitive rather than a theoretical manner.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
THE PHILOSOPHY OF EXPERIMENTATION
Why Design Experiments?
Organizing the Experiment
The Neglected Response Variable
STATISTICAL EXPERIMENTAL DESIGN
The Factorial 2-Level Design
Fractional Factorials at 2 Levels
Multi-Level Designs
3-Level Designs
Blocking in Factorial Designs
Randomized Block and Latin Square
Nested Designs
Evolutionary Operation
SORTING THE SIGNAL FROM THE NOISE
Simple Analysis
Analysis of Means by Using the Variance
YATES Algorithm
Matix Algebra
Least Squares Analysis
Putting ANOVA and Least Squares to Work
ANOVA for Blocked and Nested Designs
THE DERIVATION OF EMPIRICAL EQUATIONS FROM STATISTICALLY DESIGNED EXPERIMENTS
A Case History of an Experimental Investigation
UTILIZATION OF EMPIRICAL EQUATIONS
Monte Carlo Simulation
Case History Completed: The Utilization of the Equation
Appendix: Statistical Tables
Book by None
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