Visual Six Sigma : Making Data Analysis Lean.

Cover -- Title Page -- Copyright -- Contents -- Preface to the Second Edition -- Preface to the First Edition -- Acknowledgments -- About the Authors -- Part One Background -- Chapter 1 Introduction -- What Is Visual Six Sigma? -- Chapter 2 Six Sigma and Visual Six Sigma -- Background: Models, Data, and Variation -- Models -- Measurements -- Observational versus Experimental Data -- Six Sigma -- Variation and Statistics -- Making Detective Work Easier through Dynamic Visualization -- Visual Six Sigma: Strategies, Process, Roadmap, and Guidelines -- Conclusion -- Notes -- Chapter 3 A First Look at JMP -- The Anatomy of JMP -- Visual Displays and Analyses Featured in the Book -- Scripts -- Personalizing JMP -- Visual Six Sigma Data Analysis Process and Roadmap -- Techniques Illustrated in the Remaining Chapters -- Conclusion -- Notes -- Chapter 4 Managing Data and Data Quality -- Data Quality for Visual Six Sigma -- The Collect Data Step -- Example 1: Domestic Power Consumption -- Example 2: Biscuit Sales -- Conclusion -- Notes -- Part Two Case Studies -- Chapter 5 Reducing Hospital Late Charge Incidents -- Framing the Problem -- Collecting Data -- Uncovering Relationships -- Uncovering the Hot Xs -- Identifying Projects -- Conclusion -- Chapter 6 Transforming Pricing Management in a Chemical Supplier -- Setting the Scene -- Framing the Problem: Understanding the Current State Pricing Process -- Collecting Baseline Data -- Uncovering Relationships -- Modeling Relationships -- Revising Knowledge -- Utilizing Knowledge: Sustaining the Benefits -- Conclusion -- Chapter 7 Improving the Quality of Anodized Parts -- Setting the Scene -- Framing the Problem -- Collecting Data -- Uncovering Relationships -- Locating the Team on the VSS Roadmap -- Modeling Relationships -- Revising Knowledge -- Utilizing Knowledge -- Conclusion -- Notes.

Chapter 8 Informing Pharmaceutical Sales and Marketing -- Setting the Scene -- Collecting the Data -- Validating and Scoping the Data -- Uncovering Relationships -- Investigating Promotional Activity -- A Deeper Understanding of Regional Differences -- Summary -- Conclusion -- Note -- Chapter 9 Improving a Polymer Manufacturing Process -- Setting the Scene -- Framing the Problem -- Reviewing Historical Data -- Measurement System Analysis (MSA) -- Uncovering Relationships -- Modeling Relationships -- Revising Knowledge -- Utilizing Knowledge -- Conclusion -- Notes -- Chapter 10 Classification of Cells -- Setting the Scene -- Framing the Problem and Collecting the Data: The Wisconsin Breast Cancer Diagnostic Data Set -- Initial Data Exploration -- Constructing the Training, Validation, and Test Sets -- Prediction Models -- Recursive Partitioning -- Stepwise Logistic Model -- Generalized Regression -- Neural Net Models -- Comparison of Classification Models -- Conclusion -- Notes -- Part Three Supplementary Material -- Chapter 11 Beyond "Point and Click" with JMP -- Programming and Application Building in JMP -- A Motivating Example: Democracy and Trade Policy -- Building the Missing Data Application -- Conclusion -- Notes -- Index -- EULA.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.