Experimental Design with Applications in Management, Engineering and the Sciences / Edition 1

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Overview

Based on decades of teaching, consulting, and industrial experience in the field of design and analysis of experiments, the authors provide an intuitive understanding of the principles of experimental design and analysis. The emphasis is on the application of experimental design concepts in such traditional management and industrial engineering areas such as marketing, operations, management information systems, organizational behavior, and others. The authors also apply this material to such non-profit areas as education, health care, and government. Using popular analytical tools such as SPSS, JMP, and Microsoft Excel, Berger and Maurer emphasize the modern application of experimental design to real problems.

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Product Details

  • ISBN-13: 9780534358228
  • Publisher: Cengage Learning
  • Publication date: 8/1/2001
  • Edition description: New Edition
  • Edition number: 1
  • Pages: 496
  • Product dimensions: 7.36 (w) x 9.56 (h) x 0.97 (d)

Table of Contents

1. Introduction to Experimental Design. What Is Experimentation. A Growing Interest in Experimental Design. The Six Steps of Experimental Design. Experimental Design Applications in Management. Closure. 2. One-Factor Designs and the Analysis of Variance. Corporate Environmental Behavior at Clean Air Co. (Case Illustration). One-Factor Designs. Analysis of (the) Variance (ANOVA). Example (Using EXCEL, SPSS). Forming the F-Statistic: Logic and "Derivation". A Larger Scale Example (Using JMP). Corporate Environmental Behavior at Clean Air Electric Co.-Revisited. A Comment. Exercises. 3. Some Further Issues in One-Factor Designs and Anova. Introduction. Basic Assumptions of ANOVA. Kruskal-Walls Test. Review of Hypothesis Testing. Power of the F-Test. Confidence Intervals. Exercises. 4. Multiple Comparison Testing. The Qualities of a Superior Hotel (Case Illustration). Logic of Multiple Comparison Testing. Type I Errors in Multiple Comparison Testing. Principal Example. Pairwise Comparisons. Fisher''s Least Significance Difference Test. Tukey''s Honestly Significance Difference Test. Neuman-Keuls Test. Two Other Test Comparing All Pairs of Column Means. Dunnett Test. Post Hoc/Exploratory Comparisons-The Scheffe Test. 5. Orthogonality, Orthogonal Decomposition, and Its Role in Modern Experimental Design. Planning Travel Packages at Joyful Voyages, Inc. (Case Illustration). Introduction. Forming an Orthogonal Matrix. First Example-Portfolio Rating. Drug Example. Amended Drug Example. An Example Using SPSS. Planning Travel Packages at Joyful Voyages, Inc. - Revisited. Exercises. 6. Two Factor Cross-Classification Designs. Planning Travel Packages at Joyful voyages, Inc., A Second Look (Case Illustration). Introduction to Studying Two Factors. Designs with Replication. The Model. Parameter Estimates. Interaction Effects. Example analysis Using Excel. Example Analysis Using SPSS. A larger Example-First United Federal Bank of Boston (Using JMP). Fixed Levels VS. Random Levels. An Interesting Application of "Two Factors With Replication" Model. Two Factors With No Replication (And No Interaction). Example Analysis Using Excel. Example Analysis Using SPSS. Blocking. Friedman Non-parametric Test. Planning Travel Packages at Joyful Voyages, Inc., A Second Look-Revisited. Exercises. 7. Nested (Hierarchical) Designs. Shaving Cream Efficiency at American Razor Corporation (Case Illustration). Introduction to Nested Designs. The Model. A Numerical Example. Software/Professor Example Using JMP. A Larger Scale Example (First United Bank of Boston-using JMP). Discussion. Shaving Cream Efficiency at American Razor Corporation-Revisited. Exercises. 8. Designs with Three or More Factors-Latin Squares Designs. Maximizing Profits at Nature''s Land Farms (Case Illustration). Introduction to Multi-Factor Designs. Latin Square Model and ANOVA. Example Latin-Square Analysis. Latin-Square Example Using SPSS. Latin-Square Example Using JMP. Graeco-Latin Square Designs. Other Designs With Three or More Factors. Maximizing Profits at Nature''s Land Farms-Revisited. Exercises. 9. Two-Level Factorial Designs. Pricing A Supplemental Medical/Health Benefit Offer at Healthmark Insurance. Co. (Case Illustration). Introduction. Two Factor Experiments. Remarks on Effects and Interactions. Symbolism, Notation, and Language. Table of Signs. Four Examples. Modern Notation and Yates''s Order. Three Factors, Each at Two Levels. Example-Response Rate. Number and Kinds of Effects. Yates''s Forward Algorithm. A Note on Replicated 2k Experiments. SPSS Example. JMP Example. Main Effects in the Face of Large Interaction Effects. Levels of Factors. Factorial Designs vs. Designs Varying Factors One-at-a-Time. Factors Not Studied. Errors in Estimates in 2k Factorial Designs. A Comment on Testing the Effects in 2k Designs. Pricing a Supplemental Medical/Health Benefit Offer at Healthmark Insurance. Co. -Revisited. Exercises. 10. Confounding/Blocking in 2k Deigns. Pricing a Supplemental Medical/Health Benefit Offer at Healthmark Insurance Company-Phase II (Case Illustration). Introduction. Simple Confounding. Partial Confounding. Multiple Confounding. Determining the Blocks. Number of Blocks and Confounded Effects. A Comment on Calculating Effects. Pricing A Supplemental Medical/Health Benefit Offer at Healthmark Insurance Company-Phase II-Revisited. Appendix. Exercises. 11. Two-Level Fractional Factoral Designs. Managerial Decision-Making at FoodMart Supermarkets (Case Illustration). Introduction. 2k-P Designs. Four Factor, Half-Replicate Example. Five Factor, Half-Replicate Example. Yates''s Algorithm Revisited. Quarter Replicate Designs: A 25-2 Example. Orthogonality Revisited. Ad Agency Example. SPSS Example. Power And Minimum Detectable Effects in 2k-P Designs. Managerial Decision-Making at FoodMart Supermarkets-Revisited. Exercises. Appendix-Selection of a "Workable" Set of Dead Letters. 12. Designs with Factors at Three Levels. Optimal Frequency and Size of Print Ads for MegaStroe Electronics, Inc. (Case Illustration). Introduction. Design with One Factor at Three Levels. Design with Two Factors, Each at Three Levels. Illustrative Example. SPSS Example. JMP Example. One Benefit of Recognizing Non-Linearity. Three Levels vs. Two Levels. Optimal Frequency and Size of Print Ads for MegaStore Electronics, Inc.- Revisited. Unequally-Spaced Levels. A Comment. Exercises. 13. Introduction to Taguchi Methods. New Product Development at HighTech Corporation. (Case Illustration.). Introduction. Taguchi''s Quality Philosophy and "Loss Function". Control of the Variability of Performance. Taguchi Methods-Designing Fractional Factorial Designs. Experiments Without Interactions. Experiments Involving Interactions. Taguchi''s L16. Experiments Involving Nonlinearities/Factors with Three Levels. A Final Illustrative Example. Confirmation. Economic Evaluation of Proposed Solution. A Final Word on Taguchi Methods. New Product Development at High Tech Corporation - Revisited. Exercises. 14. Introduction to Response Surface Methodology. Determining an Optimal Product Price Warranty Length, and Promotional Expense at Luna Electronics, Inc. (Case Illustration). Introduction. The Underlying Philosophy of RSM. Methods of Steepest Ascent. Method of Local Exploration. Central Composite Designs. Box-Behnken Designs. Post-Experimental Methodology. Summation to This Point. Real World Example. NASA Example Using JMP. Follow-up Use of Solver to Explore a Response Surface. Determining and Optimal Product Price, Warranty Length, and Promotional Expense at Luna Electronics, Inc. -Revisited. Concluding Remark. Exercises. 15. Literature on Experimental Design, and Discussion of Some Topics Not Covered in this Text. Introduction. Literature Discussion. Discussion of Some Topics Not Covered in This Text. References. Statistical Tables. Index.

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