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Improving almost anything : ideas and essays, revised edition, Revised Edition Ideas and Essays Wiley Series in Probability and Statistics Series

Langue : Anglais

Auteur :

Couverture de l’ouvrage Improving almost anything : ideas and essays, revised edition
Features chapters from the writings of George E. P. Box, an acknowledged world leader in the application and theory of quality methodology to management, process improvement, process design, and discovery. This book includes a subject index and reference listing for easy access, and also an additional key contribution from Stu Hunter.
Foreword. My Professional Life. PART A: IMPROVING ALMOST ANYTHING. Introduction. When Murphy SpeaksListen. Changing Management Policy to Improve Quality and Productivity. Scientific Method: The Generation of Knowledge and Quality. PART B: DESIGN OF EXPERIMENTS FOR QUALITY. Introduction. Do Interactions Matter? Teaching Engineers Experimental Design with a Paper Helicopter. What Can You Find Out from Eight Experimental Runs? What Can You Find Out from Sixteen Experimental Runs? What Can You Find Out from Twelve Experimental Runs? Sequential Experimentation and Sequential Assembly of Designs. Must We Randomize Our Experiment? A Simple Way to Deal with Missing Observations from Designed Experiments. Finding Bad Values in Factorial Designs. How to Get Lucky. Dispersion Effects from Fractional Designs. The Importance of Practice in the Development of Statistics. PART C: SEQUENTIAL INVESTIGATION AND DISCOVERY. Introduction. A Demonstration of Response Surface Methods. Response Surface Methods: Some History. Statistics as a Catalyst to Learning. Experience as a Guide to Theoretical Development. The Invention of the Composite Design. Finding the Active Factors in Fractionated Screening Experiments. Follow-up Designs to Resolve Confounding in Multifactor Experiments. Projective Properties of Certain Orthogonal Arrays. Choice of Response Surface Design and Alphabetic Optimality. An Apology for Ecumenism in Statistics. PART D: CONTROL. Introduction. Six Sigma, Process Drift, Capability Indices, and Feedback Adjustment. Understanding Exponential Smoothing: A Simple Way to Forecast Sales and Inventory. Feedback Control by Manual Adjustment. Bounded Adjustment Charts. Statistical Process Monitoring and Feedback AdjustmentA Discussion. Dicrete Proportional-Integral Control with Constrained Adjustment. Dicrete Proportional-Integral Adjustment and Statistical Process Control. Selection of Sampling Interval and Action Limit for Discrete Feedback Adjustment. Use of Cusum Statistics in the Analysis of Data and in Process Monitoring. Influence of the Sampling Interval, Decision Limit, and Autocorrelation on the Average Run Length in Cusum Charts. Cumulative Score Charts. PART E: VARIANCE REDUCTION AND ROBUSTNESS. Introduction. Multiple Sources of Variation: Variance Components. The Importance of Data Transformation in Designd Experiments for Life Testing. Is Your Robust Design Procedure Robust? Split Plot Experiments. Robustness in Statistics. Split Plots for Robust Product and Process Experimentation. Designing Products that Are Robust to the ExperimentA Response Surfacem Approach. An Investigation of the Method of Accumulatin Analysis. Signal-to-Noise Ratios, Performance Criteria, and Transformations. PART F: SONG. There's No Theorem Like Bayes Theorem. It's distribution Free. I Am the Very Model of a Professor Statistical. References. Bography. Books and Articals Written by George Box from 1982 to 1999. Index.

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