Produktbild: Statistical Thinking

Statistical Thinking Improving Business Performance

Aus der Reihe SAS Institute Inc

Fr. 182.00

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Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

01.04.2012

Verlag

John Wiley & Sons

Seitenzahl

544

Maße (L/B/H)

26/18.3/3.3 cm

Gewicht

1127 g

Auflage

2. Auflage

Sprache

Englisch

ISBN

978-1-118-09477-8

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

01.04.2012

Verlag

John Wiley & Sons

Seitenzahl

544

Maße (L/B/H)

26/18.3/3.3 cm

Gewicht

1127 g

Auflage

2. Auflage

Sprache

Englisch

ISBN

978-1-118-09477-8

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Die Leseprobe wird geladen.
  • Produktbild: Statistical Thinking
  • Preface xiii

    Introduction to JMP xvii

    Part One Statistical Thinking Concepts 1

    Chapter 1 Need for Business Improvement 3

    Today's Business Realities and the Need to Improve 4

    We Now Have Two Jobs: A Model for Business Improvement 7

    New Management Approaches Require Statistical Thinking 10

    Principles of Statistical Thinking 15

    Applications of Statistical Thinking 18

    Summary 20

    Notes 20

    Chapter 2 Statistical Thinking Strategy 23

    Case Study: The Effect of Advertising on Sales 24

    Case Study: Improvement of a Soccer Team's Performance 30

    Statistical Thinking Strategy 39

    Context of Statistical Thinking: Statistics Discipline as a System 43

    Variation in Business Processes 45

    Synergy between Data and Subject Matter Knowledge 50

    Dynamic Nature of Business Processes 51

    Summary 53

    Project Update 53

    Notes 54

    Chapter 3 Understanding Business Processes 55

    Examples of Business Processes 56

    SIPOC Model for Processes 62

    Identifying Business Processes 64

    Analysis of Business Processes 65

    Systems of Processes 79

    Measurement Process 82

    Summary 87

    Project Update 88

    Notes 89

    Part Two Statistical Engineering: Frameworks and Basic Tools 91

    Chapter 4 Statistical Engineering: Tactics to Deploy Statistical Thinking 93

    Statistical Engineering 94

    Case Study: Reducing Resin Output Variation 95

    Case Study: Reducing Telephone Waiting Time at a Bank 101

    Basic Process Improvement Framework 105

    Case Study: Resolving Customer Complaints of Baby Wipe Flushability 111

    Case Study: The Realized Revenue Fiasco 117

    Basic Problem-Solving Framework 123

    DMAIC Framework 128

    DMAIC Case Study: Newspaper Accuracy 130

    Summary 137

    Project Update 137

    Notes 138

    Chapter 5 Process Improvement and Problem-Solving Tools 139

    Stratification 141

    Data Collection Tools 142

    Basic Graphical Analysis Tools 156

    Knowledge-Based Tools 172

    Process Stability and Capability Tools 205

    Summary 226

    Project Update 227

    Notes 227

    Part Three Formal Statistical Methods 229

    Chapter 6 Building and Using Models 231

    Examples of Business Models 232

    Types and Uses of Models 235

    Regression Modeling Process 238

    Building Models with One Predictor Variable 246

    Building Models with Several Predictor Variables 254

    Multicollinearity: Another Model Check 261

    Some Limitations of Using Existing Data 264

    Summary 265

    Project Update 267

    Notes 267

    Chapter 7 Using Process Experimentation to Build Models 269

    Why Do We Need a Statistical Approach? 270

    Examples of Process Experiments 273

    Statistical Approach to Experimentation 279

    Two-Factor Experiments: A Case Study 286

    Three-Factor Experiments: A Case Study 292

    Larger Experiments 299

    Blocking, Randomization, and Center Points 301

    Summary 303

    Project Update 304

    Notes 305

    Chapter 8 Applications of Statistical Inference Tools 307

    Examples of Statistical Inference Tools 310

    Process of Applying Statistical Inference 314

    Statistical Confidence and Prediction Intervals 317

    Statistical Hypothesis Tests 330

    Tests for Continuous Data 339

    Test for Discrete Data: Comparing Two or More Proportions 344

    Test for Regression Analysis: Test on a Regression Coefficient 345

    Sample Size Formulas 346

    Summary 352

    Project Update 353

    Notes 353

    Chapter 9 Underlying Theory of Statistical Inference 355

    Applications of the Theory 356

    Theoretical Framework of Statistical Inference 358

    Types of Data 363

    Probability Distributions 366

    Sampling Distributions 382

    Linear Combinations 389

    Transformations 392

    Summary 411

    Project Update 411

    Notes 412

    Chapter 10 Summary and Path Forward 413

    A Personal Case Study by Tom Pohlen 414

    Review of the Statistical Thinking Approach 420

    Text Summary 422

    Potential Next Steps to Deeper Understanding of Statistical Thinking 425

    Project Summary and Debriefing 427

    Notes 427

    Appendix A Effective Teamwork 429

    Appendix B Presentations and Report Writing 439

    Appendix C More on Surveys 445

    Appendix D More on Regression 453

    Appendix E More on Design of Experiments 467

    Appendix F More on Inference Tools 479

    Appendix G More on Probability Distributions 483

    Appendix H Process Design (Reengineering) 491

    Appendix I t Critical Values 497

    Appendix J Standard Normal Probabilities (Cumulative z Curve Areas) 499

    Index 503