{"product_id":"practitioners-guide-to-statistics-and-lean-six-sigma-for-process-improvements-hardback-9780470114940","title":"Practitioner's Guide to Statistics and Lean Six Sigma for Process Improvements (Hardback) 9780470114940","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003ePractitioner's Guide to Statistics and Lean Six Sigma for Process Improvements\u003c\/font\u003e\u003cbr\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003c\/p\u003e\n\u003cp\u003e\u003cfont size=\"4\"\u003eMikel J. Harry (Author), Prem S. Mann (Author), Ofelia C. De Hodgins (Author), Richard L. Hulbert (Author), Christopher J. Lacke (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9780470114940, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 28 January 2010\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e832 pages, Charts: 38 B\u0026amp;W, 0 Color; Photos: 3 B\u0026amp;W, 0 Color; Drawings: 114 B\u0026amp;W, 0 Color; Screen captures: 79 B\u0026amp;W, 0 Color; Tables: 0 B\u0026amp;W, 0 Color; Graphs: 174 B\u0026amp;W, 0 Color\u003cbr\u003e25.6 x 19 x 4.6 cm, 1.565 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cem\u003e\u003cfont size=\"3\"\u003e\"The book would be of use for those working in the fields of engineering, business, physics, management and finance who are already familiar with the concepts of lean six sigma.\" (\u003ci\u003eQW,\u003c\/i\u003e July 2010)\u003cbr\u003e \u003cbr\u003e\u003c\/font\u003e\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003cb\u003eThis hands-on book presents a complete understanding of Six Sigma and Lean Six Sigma through data analysis and statistical concepts\u003c\/b\u003e  \u003cp\u003eIn today's business world, Six Sigma, or Lean Six Sigma, is a crucial tool utilized by companies to improve customer satisfaction, increase profitability, and enhance productivity. \u003ci\u003ePractitioner's Guide to Statistics and Lean Six Sigma for Process Improvements\u003c\/i\u003e provides a balanced approach to quantitative and qualitative statistics using Six Sigma and Lean Six Sigma methodologies.\u003c\/p\u003e \u003cp\u003eEmphasizing applications and the implementation of data analyses as they relate to this strategy for business management, this book introduces readers to the concepts and techniques for solving problems and improving managerial processes using Six Sigma and Lean Six Sigma. Written by knowledgeable professionals working in the field today, the book offers thorough coverage of the statistical topics related to effective Six Sigma and Lean Six Sigma practices, including:\u003c\/p\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eDiscrete random variables and continuous random variables\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eSampling distributions\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eEstimation and hypothesis tests\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eChi-square tests\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eAnalysis of variance\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eLinear and multiple regression\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eMeasurement analysis\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eSurvey methods and sampling techniques\u003c\/p\u003e \u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eThe authors provide numerous opportunities for readers to test their understanding of the presented material, as the real data sets, which are incorporated into the treatment of each topic, can be easily worked with using Microsoft Office Excel, Minitab, MindPro, or Oracle's Crystal Ball software packages. Examples of successful, complete Six Sigma and Lean Six Sigma projects are supplied in many chapters along with extensive exercises that range in level of complexity. The book is accompanied by an extensive FTP site that features manuals for working with the discussed software packages along with additional exercises and data sets. In addition, numerous screenshots and figures guide readers through the functional and visual methods of learning Six Sigma and Lean Six Sigma.\u003c\/p\u003e \u003cp\u003e\u003ci\u003ePractitioner's Guide to Statistics and Lean Six Sigma for Process Improvements\u003c\/i\u003e is an excellent book for courses on Six Sigma and statistical quality control at the upper-undergraduate and graduate levels. It is also a valuable reference for professionals in the fields of engineering, business, physics, management, and finance.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003ePreface.  \u003cp\u003e\u003cb\u003e1 Principles of Six Sigma.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Overview.\u003c\/p\u003e \u003cp\u003e1.2 Six Sigma Essentials.\u003c\/p\u003e \u003cp\u003e1.2.1 Driving Need.\u003c\/p\u003e \u003cp\u003e1.2.2 Customer Focus.\u003c\/p\u003e \u003cp\u003e1.2.3 Core Beliefs.\u003c\/p\u003e \u003cp\u003e1.2.4 Deterministic Reasoning.\u003c\/p\u003e \u003cp\u003e1.2.5 Leverage Principle.\u003c\/p\u003e \u003cp\u003e1.3 Quality Definition.\u003c\/p\u003e \u003cp\u003e1.4 Value Creation.\u003c\/p\u003e \u003cp\u003e1.4.1 Value.\u003c\/p\u003e \u003cp\u003e1.5 Business, Operations, Process and Individual (BOPI) Goals.\u003c\/p\u003e \u003cp\u003e1.5.1 Differences between Product and Process Capability from a Six Sigma Perspective.\u003c\/p\u003e \u003cp\u003e1.6 Underpinning Economics.\u003c\/p\u003e \u003cp\u003e1.6.1 Sigma Benchmarking.\u003c\/p\u003e \u003cp\u003e1.6.2 Breakthrough Goals.\u003c\/p\u003e \u003cp\u003e1.6.3 Performance Benchmark.\u003c\/p\u003e \u003cp\u003e1.7 Performance Metrics.\u003c\/p\u003e \u003cp\u003e1.8 Process.\u003c\/p\u003e \u003cp\u003e1.8.1 Process Models.\u003c\/p\u003e \u003cp\u003e1.9 Design Complexity.\u003c\/p\u003e \u003cp\u003e1.10 Nature and Purpose of Six Sigma.\u003c\/p\u003e \u003cp\u003e1.10.1 Not Just Defect Reduction.\u003c\/p\u003e \u003cp\u003e1.11 Needs That Underlie Six Sigma.\u003c\/p\u003e \u003cp\u003e1.11.1 Looking Across the Organization.\u003c\/p\u003e \u003cp\u003e1.11.2 Processing for Six Sigma.\u003c\/p\u003e \u003cp\u003e1.11.3 Designing for Six Sigma.\u003c\/p\u003e \u003cp\u003e1.11.4 Managing for Six Sigma.\u003c\/p\u003e \u003cp\u003e1.11.5 Risk Orientation.\u003c\/p\u003e \u003cp\u003e1.12 Why Focusing on The Customer is Essential to Six Sigma.\u003c\/p\u003e \u003cp\u003e1.13 Success Factors.\u003c\/p\u003e \u003cp\u003e1.14 Software Applications.\u003c\/p\u003e \u003cp\u003eExplore Excel.\u003c\/p\u003e \u003cp\u003eExplore MINITAB.\u003c\/p\u003e \u003cp\u003eExplore JMP.\u003c\/p\u003e \u003cp\u003eGlossary.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Six Sigma Installation.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Overview.\u003c\/p\u003e \u003cp\u003e2.2 Six Sigma Leadership-The Fuel of Six Sigma.\u003c\/p\u003e \u003cp\u003e2.3 Deployment Planning.\u003c\/p\u003e \u003cp\u003e2.3.1 Executive Management.\u003c\/p\u003e \u003cp\u003e2.3.2 Six Sigma Champion.\u003c\/p\u003e \u003cp\u003e2.3.3 Line Management.\u003c\/p\u003e \u003cp\u003e2.3.4 Master Black Belts.\u003c\/p\u003e \u003cp\u003e2.3.5 Black Belts.\u003c\/p\u003e \u003cp\u003e2.3.6 Green Belts.\u003c\/p\u003e \u003cp\u003e2.3.7 White Belts.\u003c\/p\u003e \u003cp\u003e2.3.8 Six Sigma Roadmap.\u003c\/p\u003e \u003cp\u003e2.3.9 Characteristics of Effective Metrics.\u003c\/p\u003e \u003cp\u003e2.3.10 The Role of Metrics.\u003c\/p\u003e \u003cp\u003e2.3.11 Six Sigma Performance Metrics.\u003c\/p\u003e \u003cp\u003e2.3.12 Profit and Measurement\u003c\/p\u003e \u003cp\u003e2.3.13 Twelve Criteria for Performance Metrics.\u003c\/p\u003e \u003cp\u003e2.4 Application Projects.\u003c\/p\u003e \u003cp\u003e2.5 Deployment Timeline.\u003c\/p\u003e \u003cp\u003e2.6 Design for Six Sigma [DFSS] Principles.\u003c\/p\u003e \u003cp\u003e2.7 Processing for Six Sigma [PFSS] Principles.\u003c\/p\u003e \u003cp\u003e2.8 Managing for Six Sigma [MPSS] Principles.\u003c\/p\u003e \u003cp\u003e2.9 Project Review.\u003c\/p\u003e \u003cp\u003e2.9.1 Tollgate Criteria.\u003c\/p\u003e \u003cp\u003e2.9.2 Project Closure.\u003c\/p\u003e \u003cp\u003e2.9.3 Project Documentation.\u003c\/p\u003e \u003cp\u003e2.9.4 Personal Recognition.\u003c\/p\u003e \u003cp\u003e2.9.5 Authenticating Agent.\u003c\/p\u003e \u003cp\u003e2.10 Summary.\u003c\/p\u003e \u003cp\u003eGlossary.\u003c\/p\u003e \u003cp\u003eReferences and Notes.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Lean Sigma Projects.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Overview.\u003c\/p\u003e \u003cp\u003e3.2 Introduction.\u003c\/p\u003e \u003cp\u003e3.3 Project Description.\u003c\/p\u003e \u003cp\u003e3.4 Project Guidelines.\u003c\/p\u003e \u003cp\u003e3.5 Project Selection.\u003c\/p\u003e \u003cp\u003e3.5.1 Project Selection Guidelines.\u003c\/p\u003e \u003cp\u003e3.6 Project Scope.\u003c\/p\u003e \u003cp\u003e3.7 Project Leadership.\u003c\/p\u003e \u003cp\u003e3.8 Project Teams.\u003c\/p\u003e \u003cp\u003e3.9 Project Financials.\u003c\/p\u003e \u003cp\u003e3.10 Project Management.\u003c\/p\u003e \u003cp\u003e3.11 Project Payback.\u003c\/p\u003e \u003cp\u003e3.12 Project Milestones.\u003c\/p\u003e \u003cp\u003e3.13 Project Roadmap.\u003c\/p\u003e \u003cp\u003e3.14 Project Charters (General).\u003c\/p\u003e \u003cp\u003e3.15 Six Sigma Projects.\u003c\/p\u003e \u003cp\u003e3.16 Project Summary.\u003c\/p\u003e \u003cp\u003eGlossary.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Lean Practices.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Overview.\u003c\/p\u003e \u003cp\u003e4.2 Introduction.\u003c\/p\u003e \u003cp\u003e4.3 The Idea of Lean Thinking.\u003c\/p\u003e \u003cp\u003e4.4 Theory of Constraints [TOC].\u003c\/p\u003e \u003cp\u003e4.5 Lean Concept.\u003c\/p\u003e \u003cp\u003e4.6 Value-Added Versus Non-Value-Added Activities.\u003c\/p\u003e \u003cp\u003e4.7 Why Companies Think Lean.\u003c\/p\u003e \u003cp\u003e4.8 Visual Controls-Visual Factory.\u003c\/p\u003e \u003cp\u003e4.9 The Idea of Pull (Kanban).\u003c\/p\u003e \u003cp\u003e4.10 5S-6S Approach.\u003c\/p\u003e \u003cp\u003e4.11 The Idea of Perfection (Kaizen).\u003c\/p\u003e \u003cp\u003e4.12 Replication-Translate.\u003c\/p\u003e \u003cp\u003e4.13 Poka-Yoke System-Mistakeproofing.\u003c\/p\u003e \u003cp\u003e4.14 SMED System.\u003c\/p\u003e \u003cp\u003e4.15 7W + 1 Approach-Seven Plus One Deadly Waste(s).\u003c\/p\u003e \u003cp\u003e4.16 6M Approach.\u003c\/p\u003e \u003cp\u003e4.17 Summary.\u003c\/p\u003e \u003cp\u003eGlossary.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Value Stream Mapping.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Overview.\u003c\/p\u003e \u003cp\u003e5.2 Introduction.\u003c\/p\u003e \u003cp\u003e5.3 Value Stream Mapping.\u003c\/p\u003e \u003cp\u003e5.3.1 Waste Review.\u003c\/p\u003e \u003cp\u003e5.3.2 Value-Added and Non-Value-Added Activities.\u003c\/p\u003e \u003cp\u003e5.3.3 Elements of a Value Stream Map.\u003c\/p\u003e \u003cp\u003e5.4 Focused Brainstorming.\u003c\/p\u003e \u003cp\u003e5.5 Graphical representation of a Process in a Value Stream Map.\u003c\/p\u003e \u003cp\u003e5.6 Effective Working Time.\u003c\/p\u003e \u003cp\u003e5.7 Customer Demand.\u003c\/p\u003e \u003cp\u003e5.8 Takt Time.\u003c\/p\u003e \u003cp\u003e5.9 Pitch Time.\u003c\/p\u003e \u003cp\u003e5.10 Queuing Time.\u003c\/p\u003e \u003cp\u003e5.11 Cycle Time.\u003c\/p\u003e \u003cp\u003e5.12 Total Cycle Time.\u003c\/p\u003e \u003cp\u003e5.13 Calculation of Total Lead Time(s).\u003c\/p\u003e \u003cp\u003e5.14 Value-Added Percentage and Six Sigma Level.\u003c\/p\u003e \u003cp\u003e5.15 Drawing the Current-Value-Stream Map.\u003c\/p\u003e \u003cp\u003e5.15.1 Drawing Tips.\u003c\/p\u003e \u003cp\u003e5.15.2 Common Failure Modes.\u003c\/p\u003e \u003cp\u003e5.15.3 Common Definitions.\u003c\/p\u003e \u003cp\u003e5.16 Drawing the Value Stream Map.\u003c\/p\u003e \u003cp\u003e5.17 What Makes a Value Stream Lean.\u003c\/p\u003e \u003cp\u003e5.18 The Future Value Stream Map.\u003c\/p\u003e \u003cp\u003e5.19 Summary.\u003c\/p\u003e \u003cp\u003eGlossary.\u003c\/p\u003e \u003cp\u003eReferences and Notes.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Introductory Statistics and Data.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Overview.\u003c\/p\u003e \u003cp\u003e6.2 Introduction.\u003c\/p\u003e \u003cp\u003e6.3 Genetic Code of Statistics.\u003c\/p\u003e \u003cp\u003e6.4 Population and Samples.\u003c\/p\u003e \u003cp\u003e6.5 The Idea of Data.\u003c\/p\u003e \u003cp\u003e6.6 Nature of Data.\u003c\/p\u003e \u003cp\u003e6.6.1 Quantitative Variables and Data.\u003c\/p\u003e \u003cp\u003e6.6.2 Qualitative\/Categorical Variables and Data.\u003c\/p\u003e \u003cp\u003e6.7 Data Collection.\u003c\/p\u003e \u003cp\u003e6.8 The Importance of Data Collection.\u003c\/p\u003e \u003cp\u003e6.8.1 Control Cards.\u003c\/p\u003e \u003cp\u003e6.8.2 Data Collection Sheet.\u003c\/p\u003e \u003cp\u003e6.9 Sampling in Six Sigma.\u003c\/p\u003e \u003cp\u003e6.9.1 Random Sampling.\u003c\/p\u003e \u003cp\u003e6.9.2 Sequential Sampling.\u003c\/p\u003e \u003cp\u003e6.9.3 Stratified Sampling.\u003c\/p\u003e \u003cp\u003e6.10 Sources of Data.\u003c\/p\u003e \u003cp\u003e6.11 Database.\u003c\/p\u003e \u003cp\u003e6.12 Summary.\u003c\/p\u003e \u003cp\u003eGlossary.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Quality Tools.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Overview.\u003c\/p\u003e \u003cp\u003e7.2 Introduction.\u003c\/p\u003e \u003cp\u003e7.3 Nature of Six Sigma Variables.\u003c\/p\u003e \u003cp\u003e7.3.1 CT Concept.\u003c\/p\u003e \u003cp\u003e7.3.2 CTQ and CTP Characteristics.\u003c\/p\u003e \u003cp\u003e7.3.3 CTX Tree (Process Tree).\u003c\/p\u003e \u003cp\u003e7.3.4 CTY Tree (Process Tree).\u003c\/p\u003e \u003cp\u003e7.3.5 The Focus of Six Sigma.\u003c\/p\u003e \u003cp\u003e7.3.6 The Leverage Principle.\u003c\/p\u003e \u003cp\u003e7.4 Quality Function Deployment (QFD).\u003c\/p\u003e \u003cp\u003e7.5 Scales of Measurement.\u003c\/p\u003e \u003cp\u003e7.5.1 Likert Scale.\u003c\/p\u003e \u003cp\u003e7.5.2 Logarithm Scale.\u003c\/p\u003e \u003cp\u003e7.6 Diagnostic Tools.\u003c\/p\u003e \u003cp\u003e7.6.1 Elements for Problem Solving-Diagnostic Tools and Methods.\u003c\/p\u003e \u003cp\u003e7.6.2 Problem Definition-Defining Project Objective.\u003c\/p\u003e \u003cp\u003e7.7 Analytical Methods.\u003c\/p\u003e \u003cp\u003e7.7.1 Cause-Effect (CE) Analysis.\u003c\/p\u003e \u003cp\u003e7.7.2 Failure Mode-Effects Analysis (FMEA)\u003c\/p\u003e \u003cp\u003e7.7.3 \u003ci\u003eXY\u003c\/i\u003e Matrix.\u003c\/p\u003e \u003cp\u003e7.8 Graphical Tools.\u003c\/p\u003e \u003cp\u003e7.8.1 Graphical Summary.\u003c\/p\u003e \u003cp\u003e7.8.2 Boxplot or Box-and-Whisker Plot.\u003c\/p\u003e \u003cp\u003e7.8.3 Normal Probability Plot.\u003c\/p\u003e \u003cp\u003e7.8.4 Main-Effects Plot.\u003c\/p\u003e \u003cp\u003e7.8.5 Pareto Chart.\u003c\/p\u003e \u003cp\u003e7.8.6 Run Chart.\u003c\/p\u003e \u003cp\u003e7.8.7 Time-Series Plot.\u003c\/p\u003e \u003cp\u003e7.8.8 Multi-Vari Charts.\u003c\/p\u003e \u003cp\u003e7.8.9 Scatterplot.\u003c\/p\u003e \u003cp\u003e7.9 Graphical Representation of a Process.\u003c\/p\u003e \u003cp\u003e7.9.1 Process Flowcharts.\u003c\/p\u003e \u003cp\u003e7.9.2 Process Mapping.\u003c\/p\u003e \u003cp\u003e7.9.3 Cross-Functional Mapping.\u003c\/p\u003e \u003cp\u003e7.9.4 Process Mapping-Deployment Diagram.\u003c\/p\u003e \u003cp\u003e7.10 SIPOC Diagram.\u003c\/p\u003e \u003cp\u003e7.11 IPO Diagram-General Model of a Process System.\u003c\/p\u003e \u003cp\u003e7.12 Force-Field Analysis.\u003c\/p\u003e \u003cp\u003e7.13 Matrix Analysis-The Importance of Statistical Thinking.\u003c\/p\u003e \u003cp\u003e7.14 Checksheets.\u003c\/p\u003e \u003cp\u003e7.15 Scorecards.\u003c\/p\u003e \u003cp\u003e7.16 Affinity Diagram.\u003c\/p\u003e \u003cp\u003e7.17 Concept Integration.\u003c\/p\u003e \u003cp\u003eGlossary.\u003c\/p\u003e \u003cp\u003eReference.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Making Sense of Data in Six Sigma and Lean.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Overview.\u003c\/p\u003e \u003cp\u003e8.2 Summarizing Quantitative Data: Graphical Methods.\u003c\/p\u003e \u003cp\u003e8.2.1 Analytical Charts.\u003c\/p\u003e \u003cp\u003e8.2.2 Dotplots.\u003c\/p\u003e \u003cp\u003e8.2.3 Stem-and-Leaf Plots.\u003c\/p\u003e \u003cp\u003e8.2.4 Frequency Tables.\u003c\/p\u003e \u003cp\u003e8.2.5 Histograms and Performance Histograms.\u003c\/p\u003e \u003cp\u003e8.2.6 Run Charts.\u003c\/p\u003e \u003cp\u003e8.2.7 Time-Series Plots.\u003c\/p\u003e \u003cp\u003e8.3 Summarizing Quantitative Data: Numerical Methods.\u003c\/p\u003e \u003cp\u003e8.3.1 Measures of Center.\u003c\/p\u003e \u003cp\u003e8.3.2 Measures of Variation.\u003c\/p\u003e \u003cp\u003e8.3.3 Identifying Potential Outliers.\u003c\/p\u003e \u003cp\u003e8.3.4 Measures of Position and the Idea of \u003ci\u003ez\u003c\/i\u003e Scores in Six Sigma.\u003c\/p\u003e \u003cp\u003e8.3.5 Measure of Spread and Lean Sigma.\u003c\/p\u003e \u003cp\u003e8.4 Organizing and Graphing Qualitative Data.\u003c\/p\u003e \u003cp\u003e8.4.1 Organizing Qualitative Data.\u003c\/p\u003e \u003cp\u003e8.4.2 Graphing Qualitative Data.\u003c\/p\u003e \u003cp\u003e8.4.3 Pareto Analysis with Lorenz Curve.\u003c\/p\u003e \u003cp\u003e8.5 Summarizing Bivariate Data.\u003c\/p\u003e \u003cp\u003e8.5.1 Scatterplot.\u003c\/p\u003e \u003cp\u003e8.5.2 Correlation Coefficient.\u003c\/p\u003e \u003cp\u003e8.6 Multi-Vari Charts.\u003c\/p\u003e \u003cp\u003eGlossary.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Fundamentals of Capability and Rolled Throughput Yield.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Overview.\u003c\/p\u003e \u003cp\u003e9.2 Introduction.\u003c\/p\u003e \u003cp\u003e9.3 Why Capability.\u003c\/p\u003e \u003cp\u003e9.3.1 Performance Specifications.\u003c\/p\u003e \u003cp\u003e9.3.2 Fundamental Concepts of Defect-Based Measurement.\u003c\/p\u003e \u003cp\u003e9.4 Six Sigma Capability Metric.\u003c\/p\u003e \u003cp\u003e9.4.1 Criteria for Performance Metrics.\u003c\/p\u003e \u003cp\u003e9.4.2 Computing the Sigma Level from Discrete Data.\u003c\/p\u003e \u003cp\u003e9.4.3 Defective Proportions.\u003c\/p\u003e \u003cp\u003e9.4.4 Six-Sigma-Level Calculations (DPU, DPO, DPMO, PPM)-Examples.\u003c\/p\u003e \u003cp\u003e9.5 Discrete Capability.\u003c\/p\u003e \u003cp\u003e9.6 Continuous Capability-Example.\u003c\/p\u003e \u003cp\u003e9.6.1 Data Collection for Capability Studies.\u003c\/p\u003e \u003cp\u003e9.7 Fundamentals of Capability.\u003c\/p\u003e \u003cp\u003e9.8 Short- Versus Long-Term Capability.\u003c\/p\u003e \u003cp\u003e9.8.1 Short-Term Capability.\u003c\/p\u003e \u003cp\u003e9.8.2 Long-Term Capability\u003c\/p\u003e \u003cp\u003e9.8.3 Introduction to Calibrating the Shift.\u003c\/p\u003e \u003cp\u003e9.9 Capability and Performance.\u003c\/p\u003e \u003cp\u003e9.10 Indices of Capability.\u003c\/p\u003e \u003cp\u003e9.10.1 C\u003csub\u003e\u003ci\u003ep\u003c\/i\u003e\u003c\/sub\u003e Index.\u003c\/p\u003e \u003cp\u003e9.10.2 C\u003csub\u003e\u003ci\u003epk\u003c\/i\u003e\u003c\/sub\u003e Index.\u003c\/p\u003e \u003cp\u003e9.10.3 \u003ci\u003eP\u003csub\u003ep\u003c\/sub\u003e\u003c\/i\u003e Index.\u003c\/p\u003e \u003cp\u003e9.10.4 \u003ci\u003eP\u003csub\u003epk\u003c\/sub\u003e\u003c\/i\u003e Index.\u003c\/p\u003e \u003cp\u003e9.11 Calibrating the Shift.\u003c\/p\u003e \u003cp\u003e9.12 Applying the 1.5σ Shift Concept.\u003c\/p\u003e \u003cp\u003e9.13 Yield.\u003c\/p\u003e \u003cp\u003e9.13.1 Final Test Yield (FTY).\u003c\/p\u003e \u003cp\u003e9.13.2 Yield Related to Defects.\u003c\/p\u003e \u003cp\u003e9.13.3 Rolled Throughput Yield (RTY).\u003c\/p\u003e \u003cp\u003e9.13.4 In-Process Yield (IPY).\u003c\/p\u003e \u003cp\u003e9.13.5 In-Process Yield (IPY) and Rolled Throughput Yield (RTY).\u003c\/p\u003e \u003cp\u003e9.14 Hidden Factory.\u003c\/p\u003e \u003cp\u003e9.14.1 Hidden Factory Composition.\u003c\/p\u003e \u003cp\u003eGlossary.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Probability.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Overview.\u003c\/p\u003e \u003cp\u003e10.2 Experiments, Outcomes, and Sample Space.\u003c\/p\u003e \u003cp\u003e10.3 Calculating Probability.\u003c\/p\u003e \u003cp\u003e10.3.1 Equally Likely Events.\u003c\/p\u003e \u003cp\u003e10.3.2 Probability as Relative Frequency.\u003c\/p\u003e \u003cp\u003e10.3.3 Subjective Probability.\u003c\/p\u003e \u003cp\u003e10.4 Combinatorial Probability.\u003c\/p\u003e \u003cp\u003e10.5 Marginal and Conditional Probabilities.\u003c\/p\u003e \u003cp\u003e10.6 Union of Events.\u003c\/p\u003e \u003cp\u003e10.6.1 Addition Role.\u003c\/p\u003e \u003cp\u003e10.6.2 Mutually Exclusive Events.\u003c\/p\u003e \u003cp\u003e10.6.3 Complementary Events.\u003c\/p\u003e \u003cp\u003e10.7 Intersection of Events.\u003c\/p\u003e \u003cp\u003e10.7.1 Independent Versus Dependent Events.\u003c\/p\u003e \u003cp\u003e10.7.2 Multiplication Rule.\u003c\/p\u003e \u003cp\u003eGlossary.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Discrete Random Variables and Their Probability Distributions.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Overview.\u003c\/p\u003e \u003cp\u003e11.2 Six Sigma Performance Variables.\u003c\/p\u003e \u003cp\u003e11.3 Six Sigma Leverage Variables.\u003c\/p\u003e \u003cp\u003e11.4 Random Variables.\u003c\/p\u003e \u003cp\u003e11.4.1 Discrete Random Variables.\u003c\/p\u003e \u003cp\u003e11.4.2 Continuous Random Variables.\u003c\/p\u003e \u003cp\u003e11.5 Probability Distributions of a Discrete Random Variable.\u003c\/p\u003e \u003cp\u003e11.6 Mean of a Random Variable.\u003c\/p\u003e \u003cp\u003e11.7 Standard Deviation of a Discrete Random Variable.\u003c\/p\u003e \u003cp\u003e11.8 The Binomial Distribution.\u003c\/p\u003e \u003cp\u003e11.8.1 Factorials and Combinations.\u003c\/p\u003e \u003cp\u003e11.8.2 The Binomial Experiment.\u003c\/p\u003e \u003cp\u003e11.8.3 The Binomial Probability Distribution and Binomial Formula.\u003c\/p\u003e \u003cp\u003e11.8.4 Probability of Success and Shape of the Binomial Distribution.\u003c\/p\u003e \u003cp\u003e11.8.5 Mean and Standard Deviation of the Binomial Distribution.\u003c\/p\u003e \u003cp\u003e11.9 The Poisson Probability Distribution.\u003c\/p\u003e \u003cp\u003e11.9.1 Mean and Standard Deviation of the Poisson Probability Distribution.\u003c\/p\u003e \u003cp\u003e11.10 The Geometric Distribution.\u003c\/p\u003e \u003cp\u003e11.11 The Hypergeometric Probability Distribution.\u003c\/p\u003e \u003cp\u003eGlossary.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Continuous Random Variables and Their Distributions.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 Overview.\u003c\/p\u003e \u003cp\u003e12.2 Continuous Probability Distributions.\u003c\/p\u003e \u003cp\u003e12.3 The Normal Distribution.\u003c\/p\u003e \u003cp\u003e12.3.1 The Empirical Rule.\u003c\/p\u003e \u003cp\u003e12.3.2 The Standard Normal Distribution.\u003c\/p\u003e \u003cp\u003e12.3.3 Applications of the Normal Distribution.\u003c\/p\u003e \u003cp\u003e12.4 The Exponential Distribution.\u003c\/p\u003e \u003cp\u003eGlossary.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Sampling Distributions.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13.1 Overview.\u003c\/p\u003e \u003cp\u003e13.2 Sampling Distribution of a Sample Mean.\u003c\/p\u003e \u003cp\u003e13.2.1 Sampling and Nonsampling Errors.\u003c\/p\u003e \u003cp\u003e13.3 Sampling Distribution of a Sample Proportion.\u003c\/p\u003e \u003cp\u003e13.4 The Central-Limit Theorem (CLT).\u003c\/p\u003e \u003cp\u003e13.4.1 The CLT and Sampling Distribution of the Sample Mean.\u003c\/p\u003e \u003cp\u003e13.4.2 The CLT and Sampling Distribution of the Sample Proportion.\u003c\/p\u003e \u003cp\u003eGlossary.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Single-Population Estimation.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e14.1 Overview.\u003c\/p\u003e \u003cp\u003e14.2 Meaning of a Confidence Level.\u003c\/p\u003e \u003cp\u003e14.3 Estimating a Population Mean.\u003c\/p\u003e \u003cp\u003e14.3.1 Confidence Interval for a Population Mean Using the Normal Distribution.\u003c\/p\u003e \u003cp\u003e14.3.2 Confidence Interval for a Population Mean Using the \u003ci\u003et\u003c\/i\u003e Distribution.\u003c\/p\u003e \u003cp\u003e14.4 Estimating a Population Proportion.\u003c\/p\u003e \u003cp\u003e14.4.1 Traditional Large-Sample Method.\u003c\/p\u003e \u003cp\u003e14.4.2 Wilson Estimator.\u003c\/p\u003e \u003cp\u003e14.5 Estimating a Population Variance.\u003c\/p\u003e \u003cp\u003eGlossary.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Control Methods.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e15.1 Overview.\u003c\/p\u003e \u003cp\u003e15.2 Introduction.\u003c\/p\u003e \u003cp\u003e15.3 Control Logic.\u003c\/p\u003e \u003cp\u003e15.4 Statistical Control Systems.\u003c\/p\u003e \u003cp\u003e15.4.1\u003c\/p\u003e \u003cp\u003e15.5 Statistical Control.\u003c\/p\u003e \u003cp\u003e15.6 Prevention Versus Detection.\u003c\/p\u003e \u003cp\u003e15.7 A Process Control System Definition.\u003c\/p\u003e \u003cp\u003e15.8 Variation.\u003c\/p\u003e \u003cp\u003e15.8.1 Common Causes.\u003c\/p\u003e \u003cp\u003e15.8.2 Special Causes.\u003c\/p\u003e \u003cp\u003e15.9 Process Out-of-Control.\u003c\/p\u003e \u003cp\u003e15.10 Fundamentals of Process Control.\u003c\/p\u003e \u003cp\u003e15.11 Continuous Statistical Process Control (SPC) Tools.\u003c\/p\u003e \u003cp\u003e15.12 Interpreting Process Control.\u003c\/p\u003e \u003cp\u003e15.13 Statistical Process Control and Statistical Process Monitoring.\u003c\/p\u003e \u003cp\u003e15.14 The Foundation of SPC.\u003c\/p\u003e \u003cp\u003e15.15 Tools for Process Controls - Control Charts.\u003c\/p\u003e \u003cp\u003e15.16 Control Limits.\u003c\/p\u003e \u003cp\u003e15.17 Process Out-of-Control Condition.\u003c\/p\u003e \u003cp\u003e15.18 Western Electric Rules.\u003c\/p\u003e \u003cp\u003e15.19 Control Charts and How They Are Used.\u003c\/p\u003e \u003cp\u003e15.20 Precontrol Method.\u003c\/p\u003e \u003cp\u003e15.20.1 The Foundations of Precontrol.\u003c\/p\u003e \u003cp\u003e15.20.2 Precontrol Charts.\u003c\/p\u003e \u003cp\u003e15.21 Control Charts for Variables.\u003c\/p\u003e \u003cp\u003e15.21.1 \u003ci\u003eX\u003c\/i\u003e Chart.\u003c\/p\u003e \u003cp\u003e15.21.2 \u003ci\u003eR\u003c\/i\u003e Chart (Range Chart).\u003c\/p\u003e \u003cp\u003e15.21.3 \u003ci\u003eX-R\u003c\/i\u003e Chart.\u003c\/p\u003e \u003cp\u003e15.21.4 Moving Range (MR) Chart.\u003c\/p\u003e \u003cp\u003e15.21.5 Standard Deviation Chart.\u003c\/p\u003e \u003cp\u003e15.22 Control Chart for Attributes.\u003c\/p\u003e \u003cp\u003e15.22.1 \u003ci\u003ep\u003c\/i\u003e Chart.\u003c\/p\u003e \u003cp\u003e15.22.2 Control Chart-\u003ci\u003enp\u003c\/i\u003e Chart.\u003c\/p\u003e \u003cp\u003e15.22.3 \u003ci\u003ec\u003c\/i\u003e Chart.\u003c\/p\u003e \u003cp\u003e15.22.4 \u003ci\u003eu\u003c\/i\u003e Chart.\u003c\/p\u003e \u003cp\u003eGlossary.\u003c\/p\u003e \u003cp\u003eReferences and Notes.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e16 Single-Population Hypothesis Tests.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e16.1 Overview.\u003c\/p\u003e \u003cp\u003e16.2 Introduction to Hypothesis Testing.\u003c\/p\u003e \u003cp\u003e16.3 Testing a Claim About a Population Mean.\u003c\/p\u003e \u003cp\u003e16.3.1 Hypothesis Test Using the Normal Distribution.\u003c\/p\u003e \u003cp\u003e16.3.2 Hypothesis Test Using the \u003ci\u003et\u003c\/i\u003e Distribution.\u003c\/p\u003e \u003cp\u003e16.3.3 Hypothesis Test About the Median.\u003c\/p\u003e \u003cp\u003e16.4 Hypothesis Test About a Population Proportion.\u003c\/p\u003e \u003cp\u003eGlossary.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e17 Estimation and Hypothesis Tests: Two Populations.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e17.1 Overview.\u003c\/p\u003e \u003cp\u003e17.2 Inferences About the Differences Between Two Population Means for Independent Samples.\u003c\/p\u003e \u003cp\u003e17.2.1 Two-Sample \u003ci\u003et\u003c\/i\u003e Test.\u003c\/p\u003e \u003cp\u003e17.2.2 Mann-Whitney Test\u003c\/p\u003e \u003cp\u003e17.3 Inferences About the Differences Between Two Population Means for Paired Samples.\u003c\/p\u003e \u003cp\u003e17.3.1 Paired \u003ci\u003et\u003c\/i\u003e Test.\u003c\/p\u003e \u003cp\u003e17.3.2 Wilcoxon Signed-Rank Test.\u003c\/p\u003e \u003cp\u003e17.4 Inferences About the Differences Between Two Population Proportions.\u003c\/p\u003e \u003cp\u003e17.4.1 Large-Sample Procedure.\u003c\/p\u003e \u003cp\u003eGlossary.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e18 Chi-Square Tests.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e18.1 Overview.\u003c\/p\u003e \u003cp\u003e18.2 A Goodness-of-Fit Test.\u003c\/p\u003e \u003cp\u003e18.3 Contingency Tables.\u003c\/p\u003e \u003cp\u003e18.4 Tests of Independence and Homogeneity.\u003c\/p\u003e \u003cp\u003e18.4.1 Test of Independence.\u003c\/p\u003e \u003cp\u003e18.4.2 Test of Homogeneity.\u003c\/p\u003e \u003cp\u003eGlossary.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e19 Analysis of Variance.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e19.1 Overview.\u003c\/p\u003e \u003cp\u003e19.2 The \u003ci\u003eF\u003c\/i\u003e Distribution.\u003c\/p\u003e \u003cp\u003e19.3 One-Way Analysis of Variance.\u003c\/p\u003e \u003cp\u003e19.3.1 Variance Between Groups.\u003c\/p\u003e \u003cp\u003e19.3.2 Variance Within Groups.\u003c\/p\u003e \u003cp\u003e19.3.3 Total Sum of Squares (SST).\u003c\/p\u003e \u003cp\u003e19.3.4 Relationships within Sums of Squares and Degrees of Freedom.\u003c\/p\u003e \u003cp\u003e19.3.5 Equal Sample Sizes.\u003c\/p\u003e \u003cp\u003e19.3.6 Calculating the Value of the Test Statistic.\u003c\/p\u003e \u003cp\u003e19.3.7 The One-Way ANOVA Table.\u003c\/p\u003e \u003cp\u003e19.4 Pairwise Comparisons.\u003c\/p\u003e \u003cp\u003e19.5 Multi-Factor Analysis of Variance.\u003c\/p\u003e \u003cp\u003e19.5.1 Two-Way ANOVA\u003c\/p\u003e \u003cp\u003e19.5.2 \u003ci\u003eN\u003c\/i\u003e-Way ANOVA.\u003c\/p\u003e \u003cp\u003e19.6 What to Do When the Assumptions Are Unreasonable.\u003c\/p\u003e \u003cp\u003eGlossary.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e20 Linear and Multiple Regression.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e20.1 Overview.\u003c\/p\u003e \u003cp\u003e20.2 Simple Regression Model.\u003c\/p\u003e \u003cp\u003e20.3 Linear Regression.\u003c\/p\u003e \u003cp\u003e20.3.1 Simple Linear Regression.\u003c\/p\u003e \u003cp\u003e20.3.2 Scatterplots.\u003c\/p\u003e \u003cp\u003e20.3.3 Assumptions of the Regression Model.\u003c\/p\u003e \u003cp\u003e20.3.4 Standard Deviation of Random Errors.\u003c\/p\u003e \u003cp\u003e20.4 Coefficient of Determination and Correlation.\u003c\/p\u003e \u003cp\u003e20.5 Multiple Regression.\u003c\/p\u003e \u003cp\u003e20.5.1 Assumptions of the Multiple Regression Model.\u003c\/p\u003e \u003cp\u003e20.5.2 Standard Deviation of Random Errors.\u003c\/p\u003e \u003cp\u003e20.5.3 Coefficient of Multiple Determination.\u003c\/p\u003e \u003cp\u003e20.6 Regression Analysis.\u003c\/p\u003e \u003cp\u003e20.6.1 Testing for Overall Significance of Multiple Regression Model.\u003c\/p\u003e \u003cp\u003e20.6.2 Inferences about a Single Regression Coefficient, \u003ci\u003e\u003cb\u003eB\u003c\/b\u003e\u003csub\u003ei\u003c\/sub\u003e\u003c\/i\u003e.\u003c\/p\u003e \u003cp\u003e20.7 Using the Regression Model.\u003c\/p\u003e \u003cp\u003e20.8 Residual Analysis.\u003c\/p\u003e \u003cp\u003e20.9 Cautions in Using Regression.\u003c\/p\u003e \u003cp\u003e20.9.1 Determining whether a Model is Good or Bad.\u003c\/p\u003e \u003cp\u003e20.9.2 Outliers and Influential Observations.\u003c\/p\u003e \u003cp\u003e20.9.3 Multicollinearity.\u003c\/p\u003e \u003cp\u003e20.9.4 Extrapolation.\u003c\/p\u003e \u003cp\u003e20.9.5 Causality.\u003c\/p\u003e \u003cp\u003eGlossary.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e21 Measurement Analysis.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e21.1 Overview.\u003c\/p\u003e \u003cp\u003e21.2 Introduction.\u003c\/p\u003e \u003cp\u003e21.3 Measurement.\u003c\/p\u003e \u003cp\u003e21.4 Measurement Error.\u003c\/p\u003e \u003cp\u003e21.5 Accuracy and Precision.\u003c\/p\u003e \u003cp\u003e21.6 Measurement System as a Process.\u003c\/p\u003e \u003cp\u003e21.7 Categories of Measurement Error that Affect Location.\u003c\/p\u003e \u003cp\u003e21.8 Categories of Measurement that Affect Spread.\u003c\/p\u003e \u003cp\u003e21.9 Gage Accuracy and Precision.\u003c\/p\u003e \u003cp\u003e21.10 Exploring Linearity Error.\u003c\/p\u003e \u003cp\u003e21.11 Gage Repeatability and Reproducibility (R\u0026amp;R).\u003c\/p\u003e \u003cp\u003e21.11.1 Variable Gage R\u0026amp;R.\u003c\/p\u003e \u003cp\u003e21.11.2 Crossed Gage R\u0026amp;R.\u003c\/p\u003e \u003cp\u003e21.11.3 Attribute Gage R\u0026amp;R.\u003c\/p\u003e \u003cp\u003e21.12 ANOVA Method Versus X-R Method.\u003c\/p\u003e \u003cp\u003e21.13 ANOVA\/Variance Component Analysis.\u003c\/p\u003e \u003cp\u003e21.14 Rules of Thumb.\u003c\/p\u003e \u003cp\u003e21.15 Acceptability Criteria.\u003c\/p\u003e \u003cp\u003e21.16 Chapter Review.\u003c\/p\u003e \u003cp\u003eGlossary.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e22 Design of Experiments.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e22.1 Overview.\u003c\/p\u003e \u003cp\u003e22.2 Introduction.\u003c\/p\u003e \u003cp\u003e22.3 Design of Experiments (DOE)Definition.\u003c\/p\u003e \u003cp\u003e22.4 Role of Experimental Design in Process Improvement.\u003c\/p\u003e \u003cp\u003e22.5 Experiment Design Tools.\u003c\/p\u003e \u003cp\u003e22.6 Principles of an Experimental Design.\u003c\/p\u003e \u003cp\u003e22.7 Different Types of Experiments.\u003c\/p\u003e \u003cp\u003e22.7.1 Main Effects.\u003c\/p\u003e \u003cp\u003e22.8 Introduction to Factorial Designs.\u003c\/p\u003e \u003cp\u003e22.9 Features of Factorial Designs-Orthogonality.\u003c\/p\u003e \u003cp\u003e22.10 Full Factorial Designs.\u003c\/p\u003e \u003cp\u003e22.11 Residual Analysis (2\u003csup\u003e2\u003c\/sup\u003e).\u003c\/p\u003e \u003cp\u003e22.12 Modeling (2\u003csup\u003e2\u003c\/sup\u003e).\u003c\/p\u003e \u003cp\u003e22.13 Multi-Factor Experiment.\u003c\/p\u003e \u003cp\u003e22.14 Fractional Factorial Designs.\u003c\/p\u003e \u003cp\u003e22.15 The ANOVA Table.\u003c\/p\u003e \u003cp\u003e22.16 Normal Probability Plot of the Effects.\u003c\/p\u003e \u003cp\u003e22.17 Main-Effects Plot.\u003c\/p\u003e \u003cp\u003e22.18 Blocking Variable.\u003c\/p\u003e \u003cp\u003e22.19 Statistical Significance.\u003c\/p\u003e \u003cp\u003e22.20 Practical Significance.\u003c\/p\u003e \u003cp\u003e22.21 Fundamentals of Residual Analysis.\u003c\/p\u003e \u003cp\u003e22.22 Centerpoints.\u003c\/p\u003e \u003cp\u003e22.23 Noise Factors.\u003c\/p\u003e \u003cp\u003e22.24 Strategy of Good Experimentation.\u003c\/p\u003e \u003cp\u003e22.25 Selecting the Variable Levels.\u003c\/p\u003e \u003cp\u003e22.26 Selecting the Experimental Design.\u003c\/p\u003e \u003cp\u003e22.27 Replication.\u003c\/p\u003e \u003cp\u003e22.28 Analyzing the data (ANOVA).\u003c\/p\u003e \u003cp\u003e22.29 Recommendations.\u003c\/p\u003e \u003cp\u003e22.30 Achieving the Objective.\u003c\/p\u003e \u003cp\u003e22.31 Chapter Summary.\u003c\/p\u003e \u003cp\u003e22.32 Chapter Examples.\u003c\/p\u003e \u003cp\u003eGlossary.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e23 Design for Six Sigma (DFSS), Simulation, and Optimization.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e23.1 Overview.\u003c\/p\u003e \u003cp\u003e23.2 Introduction.\u003c\/p\u003e \u003cp\u003e23.3 Six Sigma as Stretch Target.\u003c\/p\u003e \u003cp\u003e23.4 Producibility.\u003c\/p\u003e \u003cp\u003e23.5 Statistical Tolerances.\u003c\/p\u003e \u003cp\u003e23.6 Design Application.\u003c\/p\u003e \u003cp\u003e23.7 Design Margin.\u003c\/p\u003e \u003cp\u003e23.8 Design Qualification.\u003c\/p\u003e \u003cp\u003e23.9 Design for Six Sigma (DFSS) Principles.\u003c\/p\u003e \u003cp\u003e23.9.1 DFSS Leverage in Product Design.\u003c\/p\u003e \u003cp\u003e23.9.2 Importance of DFSS for Product Design.\u003c\/p\u003e \u003cp\u003e23.10 Decision Power.\u003c\/p\u003e \u003cp\u003e23.11 Experimentation.\u003c\/p\u003e \u003cp\u003e23.12 Experiment Design.\u003c\/p\u003e \u003cp\u003e23.13 Response Surface Designs.\u003c\/p\u003e \u003cp\u003e23.14 Factorial Producibility.\u003c\/p\u003e \u003cp\u003e23.15 Toolbox Overview.\u003c\/p\u003e \u003cp\u003e23.16 Monte Carlo Simulations.\u003c\/p\u003e \u003cp\u003e23.16.1 Monte Carlo Simulation Defined.\u003c\/p\u003e \u003cp\u003e23.16.2 When Simulation is an Appropriate Tool.\u003c\/p\u003e \u003cp\u003e23.16.3 Defining Distributions and Outputs in Crystal Ball.\u003c\/p\u003e \u003cp\u003e23.17 Design for Six Sigma Project Selection Example.\u003c\/p\u003e \u003cp\u003e23.18 Defining Simulation Inputs.\u003c\/p\u003e \u003cp\u003e23.19 Defining Outputs and Running a Simulation.\u003c\/p\u003e \u003cp\u003e23.19.1 Analyzing a Simulation.\u003c\/p\u003e \u003cp\u003e23.20 Stochastic Optimization: Discovering the Best Portfolio with the Least Risk.\u003c\/p\u003e \u003cp\u003e23.21 Conclusions.\u003c\/p\u003e \u003cp\u003eGlossary.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e24 Survey Methods and Sampling Techniques.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e24.1 Overview.\u003c\/p\u003e \u003cp\u003e24.2 Introduction.\u003c\/p\u003e \u003cp\u003e24.3 The Sample Survey.\u003c\/p\u003e \u003cp\u003e24.4 The Survey System.\u003c\/p\u003e \u003cp\u003e24.5 Clear Goals.\u003c\/p\u003e \u003cp\u003e24.6 Target Population and Sample Size.\u003c\/p\u003e \u003cp\u003e24.7 Interviewing Method.\u003c\/p\u003e \u003cp\u003e24.8 Response Rate, Respondents and Nonrespondents.\u003c\/p\u003e \u003cp\u003e24.9 Survey Methods.\u003c\/p\u003e \u003cp\u003e24.10 Sources of Information and Data.\u003c\/p\u003e \u003cp\u003e24.11 Order of the Questions.\u003c\/p\u003e \u003cp\u003e24.12 Pilot Testing the Questionnaire.\u003c\/p\u003e \u003cp\u003e24.13 Biased Sample or Response Error.\u003c\/p\u003e \u003cp\u003e24.14 Sampling-Random and Nonrandom Samples.\u003c\/p\u003e \u003cp\u003e24.15 Population Distribution.\u003c\/p\u003e \u003cp\u003e24.16 Sampling Distribution.\u003c\/p\u003e \u003cp\u003e24.17 Sampling and Nonsampling Errors.\u003c\/p\u003e \u003cp\u003eGlossary.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix A Statistical Tables.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eTable I Table of Binomial Probabilities.\u003c\/p\u003e \u003cp\u003eTable II Standard Normal Distribution Table.\u003c\/p\u003e \u003cp\u003eTable III The \u003ci\u003et\u003c\/i\u003e Distribution Table.\u003c\/p\u003e \u003cp\u003eTable IV Chi-Square Distribution Table.\u003c\/p\u003e \u003cp\u003eTable V The \u003ci\u003eF\u003c\/i\u003e Distribution Table.\u003c\/p\u003e \u003cp\u003eTable VI Critical Values for the Mann-Whitney Test.\u003c\/p\u003e \u003cp\u003eTable VII Critical Values for the Wilcoxon Signed-Rank Test.\u003c\/p\u003e \u003cp\u003eTable VIII Sigma Conversion Table.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix B Answers to Selected Odd-Numbered Exercises.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIndex.\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Mathematics [\u003ca title=\"See our other books on Mathematics\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Mathematics%20%5BPB%5D%22\"\u003ePB\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley","offers":[{"title":"Brand New","offer_id":52257073004824,"sku":"9780470114940","price":132.39,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9780470114940.jpg?v=1781276290","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/practitioners-guide-to-statistics-and-lean-six-sigma-for-process-improvements-hardback-9780470114940","provider":"Freshly Printed Books","version":"1.0","type":"link"}