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.

Table of Contents:
1. The Experiment, the Design, and the Analysis; 1.1 Introduction; 1.2 The Experiment; 1.3 The Design; 1.4 The Analysis; 1.5 Examples; 1.6 Summary in Outline; Further Reading; Problems; 2. Review of Statistical Inference; 2.1 Introduction; 2.2 Estimation; 2.3 Tests of hypothesis; 2.4 The Operating Characterisitc Curve; 2.5 How Large a Sample?; 2.6 Application to Tests on Variances; 2.7 Application to Tests on Means; 2.8 Assessing Normality; 2.9 Applications to Tests on Proportions; 2.10 Analysis of Experiments with SAS; Further Reading; Problems; 3. Single-Factor Experiments with No Restrictions on Randomization; 3.1 Introduction; 3.2 Analysis of Variance Rationale; 3.3 After ANOVA-What?; 3.4 Tests of Means; 3.5 Confidence Limits on Means; 3.6 Components of Variance; 3.7 Checking the Model; 3.8 SAS Programs for ANOVA and Tests after ANOVA; 3.9 Summary; Further Reading; Problems; 4. Single-Factor Experiments -- Randomized Block and Latin Square Designs; 4.1 Introduction; 4.2 Randomized Complete Block Design; 4.3 ANOVA Rationale; 4.4 Missing Values; 4.5 Latin Squares; 4.6 Interpretations; 4.7 Assessing the Model; 4.8 Graeco-Latin Squares; 4.9 Extensions; 4.10 SAS Programs for Randomized Blocks and Latin Squares; 4.11 Summary; Further Reading; Problems; 5. Factorial Experiments; 5.1 Introduction; 5.2 Factorial Experiments: An Example; 5.3 Interpretations; 5.4 The Model and Its Assessment; 5.5 ANOVA Rationale; 5.6 One Observation Per Treatment; 5.7 SAS Programs for Factorial Experiments; 5.8 Summary; Further Reading; Summary; 6. Fixed, Random, and Mixed Models; 6.1 Introduction; 6.2 Single-Factor Models; 6.3 Two-Factor Models; 6.4 EMS Rule; 6.5 EMS Derivations; 6.6 The Pseudo-F Test; 6.7 Expected Mean Squares Via Statistical Computing Packages; 6.8 Remarks; 6.9 Repeatability and Reproducibility for a Measurement System; Further Reading; Problems; 7. Nested and Nested-Factorial Experiments; 7.1 Introduction; 7.2 Nested Experiments; 7.3 ANOVA Rationale; 7.4 Nested-Factorial Experiments; 7.5 Repeated-Measures Design and Nested-Factorial Experiments; 7.6 SAS Programs for Nested and Nested-Factorial Experiments; 7.7 Summary; Further Reading; Problems; 8. Experiments of Two or More Factors -- Restrictions and Randomization; 8.1 Introductin; 8.2 Factorial Experiment in a Randomized Block Design; 8.3 Factorial Experiment in a Latin Square Design; 8.4 Remarks; 8.5 SAS Programs; 8.6 Summary; Further Reading; Problems; 9.2 2 Squared Factorial; 9.3 2 Cubed Factorial; 9.4 2f Factorial; 9.5 The Yates Method; 9.6 Analysis of 2f Factorials When n=1; 9.8 Summary; Further Reading; Problems; 10. 3f Factorial Experiments; 10.1 Introduction; 10.2 3 Squared Factorial; 10.3 3 Cubed Factorial; 10.4 Computer Programs; 10.5 Summary; Further Reading; Problems; 11. Factorial Experiment -- Split-Plot Design; 11.1 Introduction; 11.2 A Split-Plot Design; 11.3 A Split-Split-Plot Design; 11.4 Using SAS to Analyze a Split-Plot Experiment; 11.5 Summary; Further Reading; Problems; 12. Factorial Experiment -- Confounding in Blocks; 12.1 Introduction; 12.2 Confounding Systems; 12.3 Block Confounding -- No Replication; 12.4 Blcok Confounding with Replication; 12.5 Confounding in 3F Factorials; 12.6 SAS Progrms; 12.7 Summary; Further Reading; Problems; 13. Fractional Replication; 13.1 Introduction; 13.2 Aliases; 13.3 2f Fractional Replication; 13.4 Plackett-Burman Designs; 14. Taguchi Approach to the Design of Experiments; 14.1 Introduction; 14.2 The L4 (2 Cubed) Orthogonal Array; 14.3 Outer Arrays; 14.4 Signal-To-Noise-Ratio; 14.5 The L8 (2 7) Orthogonal Array; 14.6 The L16 (2 15) Orthogonal Array; 14.7 The L9 (3 4) Orthogonal Array; 14.8 Some Other Taguchi Designs; 14.9 Summary; Futher Reading; Problems; 15. Regression; 15.1 Introduction; 15.2 Linear Regression; 15.3 Curvilinear Regression; 15.4 Orthogronal Polynomials; 15.5 Multiple Regression; 15.6 Summary; Further Reading; Summary; 16. Miscellaneous Topics; 16.1 Introduction; 16.2 Covariance Analysis; 16.3 Response-Surface Experimentation; 16.4 Evolutionary Operation (EVOP); 16.5 Analysis of Attribute Data; 16.6 Randomized Incomplete Blocks -- Restriction On Experimentation; 16.7 Youden Squares; Further Reading; Problems; SUMMARY AND SPECIAL PROBLEMS; GLOSSARY OF TERMS; REFERENCES; STATISTICAL TABLES; Table A Areas Under the Normal Curve; Table B Student's t Distribution; Table C Cumulative Chi-Square Distribution; Table D Cumulative F Distribution; Table E.1 Upper 5 Percent of Studentized Range q; Table E.2 Upper 1 Percent of Studentized Range q; Table F Coefficients of Orthogonal Polynomials; ANSWERS TO SELECTED PROBLEMS; INDEX