Statistical Thinking: Improving Business Performance

ISBN-13: 9781119605713 / Angielski / Twarda / 2020 / 640 str.

Roger W. Hoerl; Ron D. Snee

Spis treści

Preface xiiiIntroduction to JMP xviiPart One Statistical Thinking Concepts 1Chapter 1 Need for Business Improvement 3Today's Business Realities and the Need to Improve 4We Now Have Two Jobs: A Model for Business Improvement 8New Improvement Approaches Require Statistical Thinking 12Principles of Statistical Thinking 17Applications of Statistical Thinking 22Summary and Looking Forward 23Exercises: Chapter 1 24Notes 25Chapter 2 Data: The Missing Link 27Why Do We Need Data? 28Types of Data 29All Data are Not Created Equal 32Practical Sampling Tips to Ensure Data Quality 34What about Data Quantity? 38Every Data Set Has a Story: The Data Pedigree 40The Measurement System 42Summarizing Data 48Summary and Looking Forward 52Exercises: Chapter 2 52Notes 54Chapter 3 Statistical Thinking Strategy 55Case Study: The Effect of Advertising on Sales 56Case Study: Improvement of a Soccer Team's Performance 62Statistical Thinking Strategy 71Variation in Business Processes 76Synergy between Data and Subject Matter Knowledge 82Dynamic Nature of Business Processes 84Value of Graphics--Discovering the Unexpected 86Summary and Looking Forward 89Project Update 89Exercises: Chapter 3 90Notes 91Chapter 4 Understanding Business Processes 93Examples of Business Processes 94SIPOC Model for Processes 100Identifying Business Processes 102Analysis of Business Processes 103Systems of Processes 119Summary and Looking Forward 122Project Update 123Exercises: Chapter 4 124Notes 126Part Two Holistic Improvement: Frameworks and Basic Tools 127Chapter 5 Holistic Improvement: Tactics to Deploy Statistical Thinking 129Case Study: Resolving Customer Complaints of Baby Wipe Flushability 130The Problem-Solving Framework 137Case Study: Reducing Resin Output Variation 141The Process Improvement Framework 147Statistical Engineering 153Statistical Engineering Case Study: Predicting Corporate Defaults 154A Framework for Statistical Engineering Projects 158Summary and Looking Forward 164Project Update 165Exercises: Chapter 5 166Notes 167Chapter 6 Process Improvement and Problem-Solving Tools 169Practical Tools 172Knowledge-Based Tools 191Graphical Tools 207Analytical Tools 228Summary and Looking Forward 265Project Update 265Exercises: Chapter 6 266Notes 271Part Three Formal Statistical Methods 273Chapter 7 Building and Using Models 275Examples of Business Models 276Types and Uses of Models 279Regression Modeling Process 282Building Models with One Predictor Variable 290Building Models with Several Predictor Variables 307Multicollinearity: Another Model Check 315Some Limitations of Using Observational Data 317Summary and Looking Forward 319Project Update 321Exercises: Chapter 7 321Notes 346Chapter 8 Using Process Experimentation to Build Models 347Randomized versus Observational Studies 348Why Do We Need a Statistical Approach? 350Examples of Process Experiments 355Problem-Solving and Process Improvement are Sequential 364Statistical Approach to Experimentation 365Two-Factor Experiments: A Case Study 372Three-Factor Experiments: A Case Study 378Larger Experiments 385Blocking, Randomization, and Center Points 387Summary and Looking Forward 389Project Update 391Exercises: Chapter 8 391Notes 399Chapter 9 Applications of Statistical Inference Tools 401Examples of Statistical Inference Tools 404Process of Applying Statistical Inference 408Statistical Confidence and Prediction Intervals 412Statistical Hypothesis Tests 424Tests for Continuous Data 435Test for Discrete Data: Comparing Two or More Proportions 441Test for Regression Analysis: Test on a Regression Coefficient 442Sample Size Formulas 443Summary and Looking Forward 448Project Update 449Exercises: Chapter 9 450Notes 454Chapter 10 Underlying Theory of Statistical Inference 455Applications of the Theory 456Theoretical Framework of Statistical Inference 458Probability Distributions 463Sampling Distributions 479Linear Combinations 486Transformations 490Summary and Looking Forward 510Project Update 511Exercises: Chapter 10 511Notes 514Appendix A Effective Teamwork 515Appendix B Presentations and Report Writing 525Appendix C More on Surveys 531Appendix D More on Regression 539Appendix E More on Design of Experiments 553Appendix F More on Inference Tools 567Appendix G More on Probability Distributions 571Appendix H DMAIC Process Improvement Framework 577Appendix I t Critical Values 587Appendix J Standard Normal Probabilities (Cumulative z Curve Areas) 589Index 593

O autorze

DR. ROGER W. HOERL is an associate professor at Union College where he teaches statistics, engineering statistics, design of experiments, regression analysis, and big data analytics. Previously, he led the Applied Statistics Laboratory at GE Global Research.DR. RONALD D. SNEE is founder and president of Snee Associates, an authority on designing and implementing organizational improvement and cost-reduction solutions. Prior to this role, he worked at the DuPont Company in a variety of assignments. Snee has co-authored five books and published more than 330 articles on process improvement, quality, and statistics.