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Statistical Thinking: Improving Business Performance, 2nd Edition

Statistical Thinking Improving Business Performance, 2nd Edition

  • Author:
  • Publisher: John Wiley & Sons
  • ISBN: 9781118094778
  • Published In: April 2012
  • Format: Hardback , 511 pages
  • Jurisdiction: International ? Disclaimer:
    Countri(es) stated herein are used as reference only
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  • Description 
  • Contents 
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    How statistical thinking and methodology can help you make crucial business decisions

    Straightforward and insightful, Statistical Thinking: Improving Business Performance, Second Edition, prepares you for business leadership by developing your capacity to apply statistical thinking to improve business processes. Unique and compelling, this book shows you how to derive actionable conclusions from data analysis, solve real problems, and improve real processes. Here, you'll discover how to implement statistical thinking and methodology in your work to improve business performance.

    • Explores why statistical thinking is necessary and helpful
    • Provides case studies that illustrate how to integrate several statistical tools into the decision-making process
    • Facilitates and encourages an experiential learning environment to enable you to apply material to actual problems

    With an in-depth discussion of JMP® software, the new edition of this important book focuses on skills to improve business processes, including collecting data appropriate for a specified purpose, recognizing limitations in existing data, and understanding the limitations of statistical analyses.

  • Preface

    Part One Statistical Thinking Concepts

    Chapter 1 Need for Business Improvement

    Today's Business Realities and the Need to Improve

    We Now Have Two Jobs: A Model for Business Improvement

    New Management Approaches Require Statistical Thinking

    Principles of Statistical Thinking

    Applications of Statistical Thinking

    Summary

    Chapter 2 Statistical Thinking Strategy

    CASE STUDY: The Effect of Advertising on Sales

    CASE STUDY: Improvement of a Soccer Team's Performance

    Statistical Thinking Strategy

    Context of Statistical Thinking: Statistics Discipline as a System

    Variation in Business Processes

    Synergy Between Data and Subject Matter Knowledge

    Dynamic Nature of Business Processes

    Summary

    Project Update

    Chapter 3 Understanding Business Processes

    Examples of Business Processes

    SIPOC Model for Processes

    Identifying Business Processes

    Analysis of Business Processes

    Systems of Processes

    Measurement Process

    Summary

    Project Update

    Part Two Statistical Engineering: Frameworks and Basic Tools

    Chapter 4 Statistical Engineering: Tactics to Deploy Statistical Thinking

    Statistical Engineering

    CASE STUDY: Reducing Resin Output Variation

    CASE STUDY: Reducing Telephone Waiting Time at a Bank

    Basic Process Improvement Framework

    CASE STUDY: Resolving Customer Complaints of Baby Wipe Flushability

    CASE STUDY: The Realized Revenue Fiasco

    Basic Problem-Solving Framework

    DMAIC Framework

    DMAIC Case Study: Newspaper Accuracy

    Summary

    Project Update

    Chapter 5 Process Improvement and Problem-Solving Tools

    Stratification

    Data Collection Tools

    Basic Graphical Analysis Tools

    Knowledge-Based Tools

    Process Stability and Capability Tools

    Summary

    Project Update

    Part Three Formal Statistical Methods

    Chapter 6 Building and Using Models

    Examples of Business Models

    Types and Uses of Models

    Regression Modeling Process

    Building Models with One Predictor Variable

    Building Models with Several Predictor Variables

    Multicollinearity, another Model Check

    Some Limitations of Using Existing Data

    Summary

    Project Update

    Chapter 7 Using Process Experimentation to Build Models

    Why Do We Need a Statistical Approach?

    Examples of Process Experiments

    Statistical Approach to Experimentation

    Two-Factor Experiments: A Case Study

    Three-Factor Experiments: A Case Study

    Larger Experiments

    Blocking, Randomization, and Center Points

    Summary

    Project Update

    Chapter 8 Applications of Statistical Inference Tools

    Examples of Statistical Inference Tools

    Process of Applying Statistical Inference

    Statistical Confidence and Prediction Intervals

    Statistical Hypothesis Tests

    Tests for Continuous Data

    Test for Discrete Data: Comparing Two or More Proportions

    Test for Regression Analysis: Test on a Regression Coefficient

    Sample Size Formulas

    Summary

    Project Update

    Chapter 9 Underlying Theory of Statistical Inference

    Applications of the Theory

    Theoretical Framework of Statistical Inference

    Types of Data

    Probability Distributions

    Sampling Distributions

    Linear Combinations

    Transformations

    Summary

    Project Update

    Chapter 10 Summary and Path Forward

    A Personal Case Study by Tom Pohlen

    Review of the Statistical Thinking Approach

    Text Summary

    Potential Next Steps to Deeper Understanding of Statistical Thinking

    Project Summary and Debriefing

    Appendices

    Appendix A Effective Teamwork

    Appendix B Presentations and Report Writing

    Appendix C More on Surveys

    Appendix D More on Regression

    Appendix E More on Design of Experiments

    Appendix F More on Inference Tools

    Appendix G More on Probability Distribution

    Appendix H Process Design (Reengineering)

    Appendix I t Critical Values

    Appendix J Standard Normal Probabilities (Cumulative z Curve Areas)

    Index

  • ROGER HOERL leads the Applied Statistics Laboratory at GE Global Research, which focuses on new product and service development within each of the GE businesses. In 2006, he received the Coolidge Fellowship from GE Global Research, honoring one scientist a year from among the four global GE Research and Development sites for lifetime technical achievement. Dr. Hoerl has authored five books in the areas of statistics and business improvement, two book chapters, and over thirty-five refereed journal articles.

    RON SNEE is founder and President of Snee Associates, an authority on designing and implementing improvement and cost reduction solutions for a variety of organizational environments. Dr. Snee has an outstanding record of leadership in process and organizational improvement in a variety of industries including pharmaceutical, biotech, clinical diagnostics, and telecommunications. Among his other achievements, he is credited with leading the design of the first company-wide continuous improvement curriculum for the global giant E. I. DuPont de Nemours. He holds a host of awards and honors, has coauthored four books, and published more than 200 articles on process improvement, quality, management, and statistics.

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