Fundamental Concepts in the Design of Experiments

Name: Fundamental Concepts in the Design of Experiments
Availability: InStock
ISBN: 9780195122732

ISBN-10: 0195122739

ISBN-13: 9780195122732

Edition: 5th 1999 (Revised)

Authors: Charles R. Hicks, Kenneth V. Turner, Kenneth V. Turner

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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…

Book details

List price: $249.99
Edition: 5th
Copyright year: 1999
Publisher: Oxford University Press, Incorporated
Publication date: 3/25/1999
Binding: Hardcover
Pages: 576
Size: 9.29" wide x 7.72" long x 1.30" tall
Weight: 2.486



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