{"product_id":"improving-almost-anything-9780471727552","title":"Improving Almost Anything","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eMasterworks in process improvement and quality technology-- by George Box and friends\u003cbr\u003e \u003cbr\u003e \u003cbr\u003e George Box has a unique ability to explain complex ideas simply and eloquently. This revised edition of his masterworks since 1982 clearly demonstrates the range of his wit and intellect. These fascinating readings represent the cornerstones in the theory and application of process improvement, product design, and process control. Readers will gain valuable insights into the fundamentals and philosophy of scientific method using statistics and how it can drive creativity and discovery.\u003cbr\u003e \u003cbr\u003e The book is divided into five key parts:\u003cbr\u003e * Part A, Some Thoughts on Quality Improvement, concerns the democratization of the scientific method and, in such papers as When Murphy Speaks--Listen, advises managers to view operation of their processes as ongoing opportunities for improvement.\u003cbr\u003e * Part B, Design of Experiments for Process Improvement, illustrates the enormous advant\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\"The author, George Box, presents statistical methods in a way that almost anyone can understand and appreciate...I cannot think of a better book.\" (\u003ci\u003eSoftware Quality Professional\u003c\/i\u003e, December 2006)  \u003cp\u003e\"…bring[s the reader]…back to the point where scientist morphs into inventor, driven by the insatiable need to make the whole of the process (from design to production) more stable and efficient.\" (\u003ci\u003eElectric Review\u003c\/i\u003e, September\/October 2006)\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003eForeword by (J. Stuart Hunter).  \u003cp\u003eFriends of George Box.\u003c\/p\u003e \u003cp\u003eMy Professional Life.\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART A: SOME THOUGHTS ON PROCESS AND QUALITY IMPROVEMENT.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIntroduction.\u003c\/p\u003e \u003cp\u003eGood Quality Costs Less? How Come?\u003c\/p\u003e \u003cp\u003eWhen Murphy Speaks—Listen.\u003c\/p\u003e \u003cp\u003eChanging Management Policy to Improve Quality and Productivity.\u003c\/p\u003e \u003cp\u003eScientific Method: The Generation of Knowledge.\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART B: DESIGN OF EXPERIMENTS FOR PROCESS IMPROVEMENT.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIntroduction.\u003c\/p\u003e \u003cp\u003eDo Interactions Matter?\u003c\/p\u003e \u003cp\u003eTeaching Engineers Experimental Design with a Paper Helicopter.\u003c\/p\u003e \u003cp\u003eWhat Can You Find Out from Eight Experimental Runs?\u003c\/p\u003e \u003cp\u003eWhat Can You Find Out from Sixteen Experimental Runs?\u003c\/p\u003e \u003cp\u003eWhat Can You Find Out from Twelve Experimental Runs?\u003c\/p\u003e \u003cp\u003eSequential Experimentation and Sequential Assembly of Designs.\u003c\/p\u003e \u003cp\u003eMust We Randomize Our Experiment?\u003c\/p\u003e \u003cp\u003eA Simple Way to Deal with Missing Observations from Designed Experiments.\u003c\/p\u003e \u003cp\u003eFinding Bad Values in Factorial Designs.\u003c\/p\u003e \u003cp\u003eHow to Get Lucky.\u003c\/p\u003e \u003cp\u003eDispersion Effects from Fractional Designs.\u003c\/p\u003e \u003cp\u003eThe Importance of Practice in the Development of Statistics.\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART C: SEQUENTIAL INVESTIGATION AND DISCOVERY.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIntroduction.\u003c\/p\u003e \u003cp\u003eA Demonstration of Response Surface Methods.\u003c\/p\u003e \u003cp\u003eResponse Surface Methods: Some History.\u003c\/p\u003e \u003cp\u003eStatistics as a Catalyst to Learning.\u003c\/p\u003e \u003cp\u003eExperience as a Guide to Theoretical Development.\u003c\/p\u003e \u003cp\u003eThe Invention of the Composite Design.\u003c\/p\u003e \u003cp\u003eFinding the Active Factors in Fractionated Screening Experiments.\u003c\/p\u003e \u003cp\u003eFollow-up Designs to Resolve Confounding in Multifactor Experiments.\u003c\/p\u003e \u003cp\u003eProjective Properties of Certain Orthogonal Arrays.\u003c\/p\u003e \u003cp\u003eChoice of Response Surface Design and Alphabetic Optimality.\u003c\/p\u003e \u003cp\u003eAn Apology for Ecumenism in Statistics.\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART D: CONTROL.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIntroduction.\u003c\/p\u003e \u003cp\u003eSix Sigma, Process Drift, Capability Indices, and Feedback Adjustment.\u003c\/p\u003e \u003cp\u003eUnderstanding Exponential Smoothing: A Simple Way to Forecast Sales and Inventory.\u003c\/p\u003e \u003cp\u003eFeedback Control by Manual Adjustment.\u003c\/p\u003e \u003cp\u003eBounded Adjustment Charts.\u003c\/p\u003e \u003cp\u003eStatistical Process Monitoring and Feedback Adjustment—A Discussion.\u003c\/p\u003e \u003cp\u003eDicrete Proportional-Integral Control with Constrained Adjustment.\u003c\/p\u003e \u003cp\u003eDicrete Proportional-Integral Adjustment and Statistical Process Control.\u003c\/p\u003e \u003cp\u003eSelection of Sampling Interval and Action Limit for Discrete Feedback Adjustment.\u003c\/p\u003e \u003cp\u003eUse of Cusum Statistics in the Analysis of Data and in Process Monitoring.\u003c\/p\u003e \u003cp\u003eInfluence of the Sampling Interval, Decision Limit, and Autocorrelation on the Average Run Length in Cusum Charts.\u003c\/p\u003e \u003cp\u003eCumulative Score Charts.\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART E: VARIANCE REDUCTION AND ROBUSTNESS.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIntroduction.\u003c\/p\u003e \u003cp\u003eMultiple Sources of Variation: Variance Components.\u003c\/p\u003e \u003cp\u003eThe Importance of Data Transformation in Designd Experiments for Life Testing.\u003c\/p\u003e \u003cp\u003eIs Your Robust Design Procedure Robust?\u003c\/p\u003e \u003cp\u003eSplit Plot Experiments.\u003c\/p\u003e \u003cp\u003eRobustness in Statistics.\u003c\/p\u003e \u003cp\u003eSplit Plots for Robust Product and Process Experimentation.\u003c\/p\u003e \u003cp\u003eDesigning Products that Are Robust to the Experiment—A Response Surfacem Approach.\u003c\/p\u003e \u003cp\u003eAn Investigation of the Method of Accumulatin Analysis.\u003c\/p\u003e \u003cp\u003eSignal-to-Noise Ratios, Performance Criteria, and Transformations.\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART F: SONG.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThere's No Theorem Like Bayes Theorem.\u003c\/p\u003e \u003cp\u003eIt's distribution Free.\u003c\/p\u003e \u003cp\u003eI Am the Very Model of a Professor Statistical.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003eBiography.\u003c\/p\u003e \u003cp\u003eBooks and Articals Written by George Box from 1982 to 2005.\u003c\/p\u003e \u003cp\u003eIndex.\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default 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