Statistics for business : data analysis and modelling

목차 (Table of Contents)

• CONTENTS
• PREFACE = xix
• Observational Data and Modelling
• PART ONE: PROCESS ANALYSIS = 3
• CHAPTER 1 DATA ANALYSES AND MODEL BUILDING: AN INTRODUCTION = 5
• 1.1 Science and Its Methods = 5
• 1.2 Science and Practical Affairs = 7
• 1.3 What Is a Process? = 7
• 1.4 Statistics in Science = 11
• 1.5 Process Analysis and Process Control = 12
• 1.6 Statistics: Listening to Processes = 14
• 1.7 Designed and Observational Studies = 17
• 1.8 Exercises = 22
• 1.9 Outline of the Book = 24
• 1.10 On Using Computers = 26
• 1.11 Supplementary Exercises for Chapter 1 = 27
• 1.12 Glossary for Chapter 1 = 27
• CHAPTER 2 PLOTTING PROCESS DATA = 29
• 2.1 Knowledge Through Data = 29
• 2.2 Sequence Plots = 30
• 2.3 Exercises = 34
• 2.4 Computer-Assisted Sequence Plots = 34
• 2.5 Exercises = 38
• 2.6 Monthly Sales Data and Seasonality = 39
• 2.7 Exercises = 42
• 2.8 Some Assembly-Line Data and Transformations = 42
• 2.9 Exercise = 47
• 2.10 Some Regional Economic Data and Analysis of Changes = 47
• 2.11 Exercise = 50
• 2.12 Some U.S. Macroeconomic Data and Seasonality = 50
• 2.13 Discussion = 51
• 2.14 Supplementary Exercises for Chapter 2 = 51
• 2.15 Glossary for Chapter 2 = 52
• CHAPTER 3 DISTRIBUTION PLOTS = 53
• 3.1 Introduction = 53
• 3.2 Dotplots = 54
• 3.3 Exercises = 56
• 3.4 Stem-and-Leaf Displays = 57
• 3.5 Exercises = 61
• 3.6 Histograms = 61
• 3.7 Exercises = 71
• 3.8 Distribution Displays versus Sequence Plots = 73
• 3.9 Exercises = 75
• 3.10 Discussion = 76
• 3.11 Supplementary Exercises for Chapter = 376
• 3.12 Glossary for Chapter 3 = 79
• CHAPTER 4 METRIC DATA SUMMARIES = 80
• 4.1 Introduction = 80
• 4.2 Statistics Based on Ordered Values = 81
• 4.3 Exercises = 87
• 4.4 Statistics Based on Moments = 88
• 4.5 Exercises = 94
• 4.6 Linear Transformations and Standardization = 94
• 4.7 Exercises = 96
• 4.8 Descriptive Statistics and the Computer = 97
• 4.9 Exercises = 98
• 4.10 An Extended Exampl-Los Angeles Traffic = 99
• 4.11 Discussion = 103
• 4.12 Supplementary Exercises for Chapter 4 = 103
• 4.13 Glossary for Chapter 4 = 104
• CHAPTER 5 DESCRIBING CATEGORICAL VARIABLES = 106
• 5.1 Introduction = 106
• 5.2 Variables = 107
• 5.3 Exercises = 110
• 5.4 Tallies = 110
• 5.5 Exercises = 113
• 5.6 Two-Way Tables = 114
• 5.7 Exercises = 116
• 5.8 Other Data Within Categories = 118
• 5.9 Exercises = 121
• 5.10 Multi-Way Tables = 123
• 5.11 Exercises = 126
• 5.12 Supplementary Exercises for Chapter 5 = 127
• 5.13 Glossary for Chapter 5 = 130
• CHAPTER 6 SUMMARIZING RELATIONSHIPS = 132
• 6.1 Introduction = 132
• 6.2 Scatterplots = 133
• 6.3 Exercises = 140
• 6.4 Correlation = 141
• 6.5 Exercises = 147
• 6.6 Limitations of Correlation = 148
• 6.7 Exercises = 153
• 6.8 Autocorrelation = 155
• 6.9 Exercises = 161
• 6.10 Pearson's $$X^2$$ Statistic for 2 x 2 Tables = 162
• 6.11 Exercises = 165
• 6.12 Reinterpretation of Pearson's $$X^2$$ = 167
• 6.13 Exercises = 169
• 6.14 Pearson's $$X^2$$ for r x c Tables = 170
• 6.15 Exercises = 171
• 6.16 Supplementary Exercises for Chapter 6 = 173
• 6.17 Glossary for Chapter 6 = 177
• CHAPTER 7 FITTING CURVES = 179
• 7.1 Models = 180
• 7.2 Illustrations of Linear Regression = 182
• 7.3 Exercises = 191
• 7.4 Illustrations of Quadratic Regression = 192
• 7.5 Exercises = 195
• 7.6 Categorical Variables = 196
• 7.7 Exercises = 199
• 7.8 Addition of a Second Metric Variable = 199
• 7.9 Exercises = 202
• 7.10 Summary of Curve Fitting by OLS = 203
• 7.11 Exercises = 208
• 7.12 Internal and External Predictiveness = 209
• 7.13 Practical Experiences = 210
• 7.14 Discussion = 212
• 7.15 Supplementary Exercises for Chapter 7 = 212
• 7.16 Glossary for Chapter 7 = 214
• Appendix A: Mechanics of Ordinary Least Squares = 215
• Appendix B: Output from Statistical Software = 217
• PART TWO: MODELLING PROCESS VARIATION = 219
• CHAPTER 8 NORMAL DISTRIBUTIONS = 221
• 8.1 Introduction = 221
• 8.2 Exercises = 223
• 8.3 The Normal Curve = 224
• 8.4 Exercises = 234
• 8.5 The Central Limit Effect = 235
• 8.6 Exercises = 239
• 8.7 Checking for Normality = 239
• 8.8 Exercises = 246
• 8.9 Supplementary Exercises for Chapter 8 = 247
• 8.10 Glossary for Chapter 8 = 248
• CHAPTER 9 CONTROL CHARTS FOR METRIC VARIABLES = 249
• 9.1 Introduction = 249
• 9.2 What Is Statistical Control? = 250
• 9.3 Mean Charts for Process Control = 251
• 9.4 Exercises = 258
• 9.5 Standard Deviation Charts for Process Control = 259
• 9.6 Exercises = 262
• 9.7 Control Charts for Process Analysis = 262
• 9.8 Applications of Control Charts in Business = 270
• 9.9 Exercises = 279
• 9.10 Discussion = 280
• 9.11 Supplementary Exercises for Chapter 9 = 281
• 9.12 Glossary for Chapter 9 = 282
• CHAPTER 10 BINOMIAL DISTRIBUTIONS = 283
• 10.1 Introduction = 283
• 10.2 Assumptions and Simulations = 284
• 10.3 Exercises = 287
• 10.4 The Binomial Distribution = 287
• 10.5 Exercises = 291
• 10.6 Runs (Optional) = 291
• 10.7 The Mean and Standard Deviation = 293
• 10.8 Exercises = 296
• 10.9 The Normal Approximation = 297
• 10.10 Exercises = 302
• 10.11 Testing Hypothesis About $$\pi$$ (Optional) = 302
• 10.12 Exercises = 307
• 10.13 Discussion = 308
• 10.14 Supplementary Exercises for Chapter 10 = 309
• 10.15 Glossary for Chapter 10 = 309
• CHAPTER 11 CONTROL CHARTS FOR BINARY VARIABLES = 310
• 11.1 Introduction = 310
• 11.2 p Charts = 311
• 11.3 Exercises = 313
• 11.4 Applications = 314
• 11.5 Exercises = 317
• 11.6 Other Control Charts = 318
• 11.7 Supplementary Exercises for Chapter 11 = 318
• 11.8 Glossary for Chapter 11 = 319
• Designed Data Analysis and Modelling
• PART THREE: DATA BY DESIGN = 323
• CHAPTER 12 DATA COLLECTION = 325
• 12.1 Simple Observation = 325
• 12.2 Surveys = 326
• 12.3 Exercises = 328
• 12.4 Experiments = 329
• 12.5 Exercises = 332
• 12.6 Comparisons = 333
• 12.7 Exercises = 337
• 12.8 Steps in Data Collection = 338
• 12.9 Exercises = 341
• 12.10 A Case Study = 342
• 12.11 Supplementary Exercises for Chapter 12 = 346
• 12.12 Glossary for Chapter 12 = 347
• CHAPTER 13 INTRODUCTION TO SURVEYS = 348
• 13.1 Introduction = 348
• 13.2 Definitions = 349
• 13.3 Exercises = 352
• 13.4 Characteristics of Probability Surveys = 353
• 13.5 Exercises = 358
• 13.6 Problems Common to All Surveys = 358
• 13.7 Exercises = 361
• 13.8 The Error Triangle = 362
• 13.9 Exercises = 363
• 13.10 Suggestions for Further Reading = 364
• 13.11 Supplementary Exercises for Chapter 13 = 365
• 13.12 Glossary for Chapter 13 = 365
• Appendix C: What Is a Survey? = 366
• CHAPTER 14 SURVEY DESIGN AND SIMPLE RANDOM SAMPLING = 377
• 14.1 Introduction = 377
• 14.2 Structure of Simple Random Sampling = 378
• 14.3 Exercises = 384
• 14.4 Interval Estimation = 386
• 14.5 Numerical Illustration = 389
• 14.6 Exercises = 391
• 14.7 Random versus Representative Samples = 393
• 14.8 Exercises = 394
• 14.9 Surveys and Forecasting = 394
• 14.10 Exercises = 395
• 14.11 A Note on Sample Sizes = 396
• 14.12 Exercises = 397
• 14.13 Supplementary Exercises for Chapter 14 = 398
• 14.14 Glossary for Chapter 14 = 399
• CHAPTER 15 READING THE RESULTS OF A SURVEY = 400
• 15.1 Introduction to the Report = 400
• 15.2 Initial Exploration of Tables = 401
• 15.3 Some Simple Interval Estimates = 404
• 15.4 Comparison of Groups Estimates, and Standard Errors, and Confidence Intervals = 409
• 15.5 Exercises = 412
• 15.6 Supplementary Exercises for Chapter 15 = 413
• Appendix D: Diagnosis-Related Groups Using Data from the National Hospital Discharge Survey: United States, 1982 = 415
• CHAPTER 16 STRATIFIED, CLUSTER AND SYSTEMATIC SAMPLING (OPTIONAL) = 426
• 16.1 Stratification in Sampling = 426
• 16.2 Mechanics of Stratified Sampling = 428
• 16.3 Exercises = 431
• 16.4 Clustering = 433
• 16.5 Systematic Sampling = 435
• 16.6 Replicated Systematic Sampling = 436
• 16.7 Supplementary Exercises for Chapter 16 = 438
• 16.8 Glossary for Chapter 16 = 438
• PART FOUR: PRINCIPLES OF PROBABILISTIC INFERENCE = 439
• CHAPTER 17 SIMULATION (OPTIONAL) = 440
• 17.1 Introduction = 440
• 17.2 Randomness = 441
• 17.3 Exercises = 446
• 17.4 Random Arithmetic (Optional) = 446
• 17.5 Exercises = 457
• 17.6 Simulating Random Walks = 458
• 17.7 Exercises = 462
• 17.8 Supplementary Exercises for Chapter 17 = 464
• 17.9 Glossary for Chapter 17 = 465
• CHAPTER 18 DISTRIBUTION FUNCTIONS AND MOMENTS (OPTIONAL) = 466
• 18.1 Introduction = 466
• 18.2 Cumulative Distributions for Data = 467
• 18.3 Exercises = 473
• 18.4 Theoretical Cumulative Distribution Functions = 474
• 18.5 Exercises = 476
• 18.6 Moments = 476
• 18.7 Exercises = 482
• 18.8 Moments of Transformed Variables = 483
• 18.9 Exercise = 486
• 18.10 Supplementary Exercises for Chapter 18 = 487
• 18.11 Glossary for Chapter 18 = 488
• CHAPTER 19 SAMPLING DISTRIBUTIONS AND SIGNIFICANCE TESTING = 489
• 19.1 Introduction = 489
• 19.2 The t Statistic for a Single Sample Mean = 489
• 19.3 Exercise = 495
• 19.4 Application to Significance Testing = 495
• 19.5 Exercises = 502
• 19.6 t Statistics for Nonnormal Processes (Optional) = 502
• 19.7 Exercises = 507
• 19.8 Chi-square Statistics = 507
• 19.9 Exercises = 514
• 19.10 Two-Sample t Statistics for the Differences Between Two Sample Means = 515
• 19.11 Exercises = 520
• 19.12 F Statistics = 520
• 19.13 Exercises = 524
• 19.14 Order Statistics = 524
• 19.15 Exercises = 527
• 19.16 p Values = 528
• 19.17 Exercises = 531
• 19.18 Supplementary Exercises for Chapter 19 = 531
• 19.19 Glossary for Chapter 19 = 532
• PART FIVE: MODELLING MANY VARIABLES = 535
• CHAPTER 20 INFERENCE IN REGRESSION MODELS = 537
• 20.1 A Statistical Model for Regression Analysis = 537
• 20.2 Interpreting the Regression Parameters = 539
• 20.3 Exercises = 540
• 20.4 Estimating Parameters = 541
• 20.5 Exercises = 542
• 20.6 Inference for Models with One Predictor = 542
• 20.7 Exercises = 554
• 20.8 Inference for Models with Many Predictors = 557
• 20.9 Exercises = 561
• 20.10 The Regression Fallacy = 563
• 20.11 Sampling Models (Or How to Inflate $$R^2$$) = 565
• 20.12 Exercises = 569
• 20.13 Binary Response Variables and Discriminant Analysis = 569
• 20.14 Exercises = 574
• 20.15 Supplementary Exercises for Chapter 20 = 575
• 20.16 Glossary for Chapter 20 = 577
• Appendix E: The Matrix Approach to Multiple Regression = 577
• CHAPTER 21 REGRESSION DIAGNOSTICS AND TRANSFORMATIONS = 580
• 21.1 Introduction = 580
• 21.2 Residuals = 581
• 21.3 Exercises = 586
• 21.4 Outliers = 587
• 21.5 Exercises = 592
• 21.6 Influential Observations = 592
• 21.7 Exercises = 598
• 21.8 Transformations = 599
• 21.9 Exercises = 608
• 21.10 A Case Study-Sex Discrimination in the Workplace? = 610
• 21.11 Logistic Regression (Optional) = 619
• 21.12 Supplementary Exercises for Chapter 21 = 620
• 21.13 Glossary for Chapter 21 = 621
• CHAPTER 22 REGRESSION MODEL SELECTION = 622
• 22.1 Introduction = 622
• 22.2 Added Variable Plots = 625
• 22.3 Exercises = 632
• 22.4 Collinearity = 633
• 22.5 Exercises = 637
• 22.6 Effects of Model Misspecification = 638
• 22.7 Exercises = 639
• 22.8 Best Subset Methods = 640
• 22.9 Exercises = 643
• 22.10 The F-test for Subsets of Coefficients (Optional) = 644
• 22.11 Exercises = 645
• 22.12 Stepwise Regression (Optional) = 645
• 22.13 Exercises = 647
• 22.14 Supplementary Exercises for Chapter 22 = 648
• 22.15 Glossary for Chapter 22 = 649
• CHAPTER 23 TIME SERIES DATA = 650
• 23.1 Introduction = 650
• 23.2 Time Series Regression = 651
• 23.3 Exercises = 664
• 23.4 Lagged Variables = 664
• 23.5 Exercises = 672
• 23.6 Autoregression = 672
• 23.7 Exercises = 680
• 23.8 Exponential Smoothing = 682
• 23.9 Exercises = 694
• 23.10 Supplementary Exercises for Chapter 23 = 694
• 23.11 Glossary for Chapter 23 = 695
• CHAPTER 24 SEASONAL TIME SERIES = 697
• 24.1 Seasonality = 697
• 24.2 Exercises = 698
• 24.3 Seasonal Indicators = 700
• 24.4 Exercises = 706
• 24.5 Seasonal Autoregression = 707
• 24.6 Exercises = 710
• 24.7 Seasonal Exponential Smoothing = 711
• 24.8 Exercises = 716
• 24.9 Seasonal Differencing = 717
• 24.10 Exercises = 719
• 24.11 Seasonal Adjustment = 720
• 24.12 Supplementary Exercises for Chapter 24 = 722
• 24.13 Glossary for Chapter 24 = 723
• Statistics in Organizations
• CHAPTER 25 A PERSPECTIVE ON STATISTICS IN ORGANIZATIONS = 726
• 25.1 Introduction = 726
• 25.2 Organizational Structure = 727
• 25.3 Science in Organizations = 729
• 25.4 Statistical Tools in Problem Formulation = 730
• 25.5 Exercises = 741
• 25.6 Organizating for Quality Improvement = 741
• 25.7 Exercises = 743
• 25.8 Supplementary Exercises for Chapter 25 = 744
• 25.9 Glossary for Chapter 25 = 745
• APPENDIX 1 TABLES = 746
• APPENDIX 2 SELECTED DATA SET LISTINGS = 753
• REFERENCES = 760
• GLOSSARY = 766
• ANSWERS TO SELECTED EXERCISES = 774
• DATA SET INDEX = 801
• INDEX = 805