Description Fundamental Concepts in the Design of Experiments, 5/e offers comprehensive coverage of the key elements of experimental design used by applied researchers to solve problems in the field. Wide-ranging and accessible, it shows students how to use applied statistics for planning, running, and analyzing experiments. Featuring over 350 problems taken from the authors' actual industrial consulting experiences, the text gives students valuable practice with real data and problem solving. The problems emphasize the basic philosophy of design and are simple enough for students with limited mathematical back grounds to understand. The authors provide extensive coverage of the analysis of residuals, the concept of resolution in fractional replications, Plackett-Burman designs, and Taguchi techniques. SAS (Statistical Analysis System) computer programs are incorporated to facilitate analysis. Thoroughly revised and updated, this new edition includes sixty new problems, focuses more on computer use (adding computer outputs from statistical packages like Minitab, SPSS, and JMP), and emphasizes graphical procedures including residual plots and normal quantile plots. Ideal for various advanced undergraduate and graduate experimental methods courses taught in statistics, engineering, and mathematics departments, this book will also appeal to professionals and researchers doing experimental work. Features Over 350 problems based on real data from the author's consulting experiments in the industry. A breadth of realistic examples, providing a wealth of material for a wide audience. Good topical coverage at a level suitable for students who do not have extensive mathematical backgrounds. Use of SAS (statistical anlaysis system) programs to analyze results of experiments at the end of nearly all chapters. The single most unique feature is the author's breadth of coverage at a very lucid. Insightful level. This is especially helpful for students whose backgrounds in math and statistics are minimal, but are required to know this material to apply it in their field. Table of Contents Preface 1. The Experiment, the Design, and the Analysis 2. Review of Statistical Inference 3. Single-Factor Experiments with No Restrictions on Randomization 4. Single-Factor Experiments: Randomized Block and Latin Square Designs 5. Factorial Experiments 6. Fixed, Random, and Mixed Models 7. Nested and Nested-Factorial Experiments 8. Experiments of Two or More Factors: Restrictions on Randomization 9. 2f Factorial Experiments 10. 3f Factorial Experiments 11. Factorial Experiment: Split-Plot Design 12. Factorial Experiment: Confounding in Blocks 13. Fractional Replication 14. The Taguchi Approach to the Design of Experiments 15. Regression 16. Miscellaneous Topics 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% of Studentized Range q Table E.2 Upper 1% of Studentized Range q Table F Coefficients of Orthogonal Polynomials