Fundamental Concepts in the Design of Experiments

ISBN-10: 0195122739

ISBN-13: 9780195122732

Edition: 5th 1999 (Revised)

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Description:

This text is a solid revision and redesign of Charles Hicks's comprehensive fourth edition of Fundamental Concepts in the Design of Experiments. It covers the essentials of experimental design used by applied researchers in solving problems in the field. It is appropriate for a variety of experimental methods courses found in engineering and statistics departments. Students learn to use applied statistics for planning, running, and analysing an experiment. The text includes 350+ problems taken from the author's actual industrial consulting experiences to give students valuable practice with real data and problem solving. About 60 new problems have been added for this edition. SAS (Statistical Analysis System) computer programs are incorporated to facilitate analysis. There is extensive coverage of the analysis of residuals, the concepts of resolution in fractional replications, the Plackett-Burman designs, and Taguchi techniques. The new edition will place a greater emphasis on computer use, include additional problems, and add computer outputs from statistical packages like Minitab, SPSS, and JMP. The book is written for anyone engaged in experimental work who has a good background in statistical inference. It will be most profitable reading to those with a background in statistical methods including analysis of variance. This text is suitable for senior undergraduate/graduate level students in mathematics, statistics, or engineering. It is appropriate for a variety of experimental methods courses found in engineering and statistics deparmtents -- majors in this course are usually in applied statistics; non-majors, in industrial and electrical engineering, or education and life sciences.
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Book details

List price: $199.95
Edition: 5th
Copyright year: 1999
Publisher: Oxford University Press, Incorporated
Publication date: 3/25/1999
Binding: Hardcover
Pages: 576
Size: 8.00" wide x 9.50" long x 1.25" tall
Weight: 2.860

Preface
The Experiment, the Design, and the Analysis
Introduction to Experimental Design
The Experiment
The Design
The Analysis
Examples
Summary in Outline
Further ReadingProblems
Review of Statistical Inference
Introduction
Estimation
Tests of Hypothesis
The Operating Characteristic Curve
How Large a Sample?
Application to Tests on Variances
Application to Tests on Means
Assessing Normality
Applications to Tests on Proportions
Analysis of Experiments with SAS
Further ReadingProblems
Single-Factor Experiments with No Restrictions on Randomization
Introduction
Analysis of Variance Rationale
After ANOVA--What?
Tests on Means
Confidence Limits on Means
Components of Variance
Checking the Model
SAS Programs for ANOVA and Tests after ANOVA
Summary
Further ReadingProblems
Single-Factor Experiments: Randomized Block and Latin Square Designs
Introduction
Randomized Complete Block Design
ANOVA Rationale
Missing Values
Latin Squares
Interpretations
Assessing the Model
Graeco-Latin Squares
Extensions
SAS Programs for Randomized Blocks and Latin Squares
Summary
Further ReadingProblems
Factorial Experiments
Introduction
Factorial Experiments: An Example
Interpretations
The Model and Its Assessment
ANOVA Rationale
One Observation Per Treatment
SAS Programs for Factorial Experiments
Summary
Further ReadingProblems
Fixed, Random, and Mixed Models
Introduction
Single-Factor Models
Two-Factor Models
EMS Rules
EMS Derivations
The Pseudo-F Test
Expected Mean Squares Via Statistical Computing Packages
Remarks
Repeatability and Reproducibility for a Measurement System
SAS Problems for Random and Mixed Models
Further ReadingProblems
Nested and Nested-Factorial Experiments
Introduction
Nested Experiments
ANOVA Rationale
Nested-Factorial Experiments
Repeated-Measures Design and Nested-Factorial Experiments
SAS Programs for Nested and Nested-Factorial Experiments
SummaryFurther ReadingProblems
Experiments of Two or More Factors: Restrictions on Randomization
Introduction
Factorial Experiment in a Randomized Block Design
Factorial Experiment in a Latin Square Design
Remarks
SAS Programs
SummaryProblems
2f Factorial Experiments
Introduction
2 Squared Factorial
2 Cubed Factorial
2f Remarks
The Yates Method
Analysis of 2f Factorials When n=1
Some Commments about Computer Use
Summary
Further ReadingProblems
3f Factorial Experiments
Introduction
3 Squared Factorial
3 Cubed Factorial
Computer Programs
SummaryProblems
Factorial Experiment: Split-Plot Design
Introduction
A Split-Plot Design
A Split-Split-Plot Design
Using SAS to Analyze a Split-Plot Experiment
Summary
Further ReadingProblems
Factorial Experiment: Confounding in Blocks
Introduction
Confounding Systems
Block Confounding, No Replication
Block Confounding with Replication
Confounding in 3F Factorials
SAS Progrms
Summary
Further ReadingProblems
Fractional Replication
Introduction
Aliases
2f Fractional Replications
Plackett-Burman Designs
Design Resolution
3f-k Fractional Factorials
SAS Programs
Summary
Further ReadingProblems
The Taguchi Approach to the Design of Experiments
Introduction
The L4 (2 Cubed) Orthogonal Array
Outer Arrays
Signal-To-Noise Ratio
The L8 (2 7) Orthogonal Array
The L16 (2 15) Orthogonal Array
The L9 (3 4) Orthogonal Array
Some Other Taguchi Designs
Summary
Further ReadingProblems
Regression
Introduction
Linear Regression
Curvilinear Regression
Orthogonal Polynomials
Multiple Regression
Summa
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