Business statistics

Cover......Page 1
Title......Page 4
Copyright......Page 5
Contents......Page 8
Preface......Page 12
Index of Applications......Page 23
 Chapter 1 Data and Decisions (E-Commerce)......Page 30
  1.1 What Are Data?......Page 31
  1.2 Variable Types......Page 35
  1.3 Data Sources: Where, How, and When......Page 38
  Ethics in Action......Page 40
  Technology Help: Data......Page 42
  Brief Case: Credit Card Bank......Page 43
 Chapter 2 Displaying and Describing Categorical Data (Keen, Inc.)......Page 48
  2.1 Summarizing a Categorical Variable......Page 49
  2.2 Displaying a Categorical Variable......Page 50
  2.3 Exploring Two Categorical Variables: Contingency Tables......Page 54
  2.4 Segmented Bar Charts and Mosaic Plots......Page 58
  2.5 Simpson’s Paradox......Page 62
  Ethics in Action......Page 65
  Technology Help: Displaying Categorical Data......Page 66
  Brief Case: Credit Card Bank......Page 68
 Chapter 3 Displaying and Describing Quantitative Data (AIG)......Page 78
  3.1 Displaying Quantitative Variables......Page 79
  3.2 Shape......Page 82
  3.3 Center......Page 85
  3.4 Spread of the Distribution......Page 87
  3.6 Standardizing Variables......Page 89
  3.7 Five-Number Summary and Boxplots......Page 91
  3.8 Comparing Groups......Page 94
  3.9 Identifying Outliers......Page 96
  3.10 Time Series Plots......Page 98
  *3.11 Transforming Skewed Data......Page 101
  Ethics in Action......Page 106
  Technology Help: Displaying and Summarizing Quantitative Variables......Page 109
  Brief Cases: Detecting the Housing Bubble and Socio-Economic Data on States......Page 111
 Chapter 4 Correlation and Linear Regression (Amazon.com)......Page 126
  4.1 Looking at Scatterplots......Page 127
  4.2 Assigning Roles to Variables in Scatterplots......Page 130
  4.3 Understanding Correlation......Page 131
  4.4 Lurking Variables and Causation......Page 135
  4.5 The Linear Model......Page 137
  4.6 Correlation and the Line......Page 138
  4.7 Regression to the Mean......Page 141
  4.8 Checking the Model......Page 143
  4.9 Variation in the Model and R2......Page 146
  4.10 Reality Check: Is the Regression Reasonable?......Page 148
  4.11 Nonlinear Relationships......Page 150
  Ethics in Action......Page 155
  Technology Help: Correlation and Regression......Page 158
  Brief Cases: Fuel Efficiency, Cost of Living, and Mutual Funds......Page 160
  Case Study I: Paralyzed Veterans of America......Page 173
 Chapter 5 Randomness and Probability (Credit Reports and the Fair Isaacs Corporation)......Page 176
  5.1 Random Phenomena and Probability......Page 177
  5.2 The Nonexistent Law of Averages......Page 179
  5.3 Different Types of Probability......Page 180
  5.4 Probability Rules......Page 182
  5.5 Joint Probability and Contingency Tables......Page 187
  5.6 Conditional Probability......Page 188
  5.7 Constructing Contingency Tables......Page 191
  5.8 Probability Trees......Page 192
  *5.9 Reversing the Conditioning: Bayes’ Rule......Page 194
  Ethics in Action......Page 196
  Technology Help: Generating Random Numbers......Page 198
  Brief Case: Global Markets......Page 199
 Chapter 6 Random Variables and Probability Models (Metropolitan Life Insurance Company)......Page 210
  6.1 Expected Value of a Random Variable......Page 211
  6.2 Standard Deviation of a Random Variable......Page 213
  6.3 Properties of Expected Values and Variances......Page 216
  6.4 Bernoulli Trials......Page 220
  6.5 Discrete Probability Models......Page 221
  Ethics in Action......Page 228
  Technology Help: Random Variables and Probability Models......Page 230
  Brief Case: Investment Options......Page 231
 Chapter 7 The Normal and Other Continuous Distributions (The NYSE)......Page 238
  7.1 The Standard Deviation as a Rule......Page 239
  7.2 The Normal Distribution......Page 241
  7.3 Normal Probability Plots......Page 249
  7.4 The Distribution of Sums of Normals......Page 250
  7.5 The Normal Approximation for the Binomial......Page 254
  7.6 Other Continuous Random Variables......Page 256
  Ethics in Action......Page 260
  Technology Help: Probability Calculations and Plots......Page 261
  Brief Case: Price/Earnings and Stock Value......Page 262
 Chapter 8 Surveys and Sampling (Roper Polls)......Page 272
  8.1 Three Ideas of Sampling......Page 273
  8.3 Common Sampling Designs......Page 277
  8.4 The Valid Survey......Page 283
  8.5 How to Sample Badly......Page 285
  Ethics in Action......Page 288
  Technology Help: Random Sampling......Page 290
  Brief Cases: Market Survey Research and The GfK Roper Reports Worldwide Survey......Page 291
 Chapter 9 Sampling Distributions and Confidence Intervals for Proportions (Marketing Credit Cards: The MBNA Story)......Page 300
  9.1 The Distribution of Sample Proportions......Page 301
  9.2 A Confidence Interval for a Proportion......Page 306
  9.3 Margin of Error: Certainty vs. Precision......Page 311
  9.4 Choosing the Sample Size......Page 315
  Ethics in Action......Page 320
  Technology Help: Confidence Intervals for Proportions......Page 322
  Brief Cases: Has Gold Lost Its Luster? and Forecasting Demand......Page 323
  Case Study II: Real Estate Simulation......Page 333
 Chapter 10 Testing Hypotheses about Proportions (Dow Jones Industrial Average)......Page 334
  10.1 Hypotheses......Page 335
  10.2 A Trial as a Hypothesis Test......Page 337
  10.3 P-Values......Page 338
  10.4 The Reasoning of Hypothesis Testing......Page 340
  10.5 Alternative Hypotheses......Page 342
  10.6 P-Values and Decisions: What to Tell about a Hypothesis Test......Page 345
  Ethics in Action......Page 349
  Technology Help: Hypothesis Tests......Page 351
  Brief Cases: Metal Production and Loyalty Program......Page 352
 Chapter 11 Confidence Intervals and Hypothesis Tests for Means (Guinness & Co.)......Page 360
  11.1 The Central Limit Theorem......Page 361
  11.2 The Sampling Distribution of the Mean......Page 364
  11.3 How Sampling Distribution Models Work......Page 366
  11.4 Gosset and the t-Distribution......Page 367
  11.5 A Confidence Interval for Means......Page 369
  11.6 Assumptions and Conditions......Page 371
  11.7 Testing Hypotheses about Means—the One-Sample t-Test......Page 377
  Ethics in Action......Page 382
  Technology Help: Inference for Means......Page 384
  Brief Cases: Real Estate and Donor Profiles......Page 386
 Chapter 12 More about Tests and Intervals (Traveler’s Insurance)......Page 396
  12.1 How to Think about P-Values......Page 398
  12.2 Alpha Levels and Significance......Page 403
  12.3 Critical Values......Page 405
  12.4 Confidence Intervals and Hypothesis Tests......Page 406
  12.5 Two Types of Errors......Page 409
  12.6 Power......Page 411
  Ethics in Action......Page 415
  Brief Case: Confidence Intervals and Hypothesis Tests......Page 416
 Chapter 13 Comparing Two Means (Visa Global Organization)......Page 424
  13.1 Comparing Two Means......Page 425
  13.3 Assumptions and Conditions......Page 428
  13.4 A Confidence Interval for the Difference Between Two Means......Page 432
  13.5 The Pooled t-Test......Page 435
  13.6 Paired Data......Page 440
  13.7 Paired t-Methods......Page 441
  Ethics in Action......Page 447
  Technology Help: Comparing Two Groups......Page 449
  Brief Cases: Real Estate and Consumer Spending Patterns (Data Analysis)......Page 452
 Chapter 14 Inference for Counts: Chi-Square Tests (SAC Capital)......Page 470
  14.1 Goodness-of-Fit Tests......Page 472
  14.2 Interpreting Chi-Square Values......Page 477
  14.3 Examining the Residuals......Page 478
  14.4 The Chi-Square Test of Homogeneity......Page 479
  14.5 Comparing Two Proportions......Page 483
  14.6 Chi-Square Test of Independence......Page 485
  Ethics in Action......Page 491
  Technology Help: Chi-Square......Page 493
  Brief Cases: Health Insurance and Loyalty Program......Page 495
  Case Study III: Investment Strategy Segmentation......Page 507
 Chapter 15 Inference for Regression (Nambé Mills)......Page 508
  15.1 A Hypothesis Test and Confidence Interval for the Slope......Page 509
  15.2 Assumptions and Conditions......Page 513
  15.3 Standard Errors for Predicted Values......Page 519
  15.4 Using Confidence and Prediction Intervals......Page 521
  Ethics in Action......Page 524
  Technology Help: Regression Analysis......Page 526
  Brief Cases: Frozen Pizza and Global Warming?......Page 527
 Chapter 16 Understanding Residuals (Kellogg’s)......Page 542
  16.1 Examining Residuals for Groups......Page 543
  16.2 Extrapolation and Prediction......Page 546
  16.3 Unusual and Extraordinary Observations......Page 549
  16.4 Working with Summary Values......Page 552
  16.5 Autocorrelation......Page 553
  16.6 Transforming (Re-expressing) Data......Page 555
  16.7 The Ladder of Powers......Page 559
  Ethics in Action......Page 566
  Technology Help: Examining Residuals......Page 567
  Brief Cases: Gross Domestic Product and Energy Sources......Page 568
 Chapter 17 Multiple Regression (Zillow.com)......Page 584
  17.1 The Multiple Regression Model......Page 586
  17.2 Interpreting Multiple Regression Coefficients......Page 588
  17.3 Assumptions and Conditions for the Multiple Regression Model......Page 590
  17.4 Testing the Multiple Regression Model......Page 598
  17.5 Adjusted R2 and the F-statistic......Page 600
  *17.6 The Logistic Regression Model......Page 602
  Ethics in Action......Page 609
  Technology Help: Regression Analysis......Page 611
  Brief Case: Golf Success......Page 613
 Chapter 18 Building Multiple Regression Models (Bolliger and Mabillard)......Page 626
  18.1 Indicator (or Dummy) Variables......Page 629
  18.2 Adjusting for Different Slopes—Interaction Terms......Page 633
  18.3 Multiple Regression Diagnostics......Page 635
  18.4 Building Regression Models......Page 641
  18.5 Collinearity......Page 649
  18.6 Quadratic Terms......Page 652
  Ethics in Action......Page 658
  Technology Help: Building Multiple Regression Models......Page 660
  Brief Case: Building Models......Page 661
 Chapter 19 Time Series Analysis (Whole Foods Market®)......Page 672
  19.1 What Is a Time Series?......Page 673
  19.2 Components of a Time Series......Page 674
  19.3 Smoothing Methods......Page 677
  19.4 Summarizing Forecast Error......Page 682
  19.5 Autoregressive Models......Page 684
  19.6 Multiple Regression–based Models......Page 690
  19.7 Choosing a Time Series Forecasting Method......Page 701
  19.8 Interpreting Time Series Models: The Whole Foods Data Revisited......Page 702
  Ethics in Action......Page 703
  Brief Cases: U.S. Trade with the European Union and Tiffany & Co.......Page 706
  Case Study IV: Health Care Costs......Page 719
 Chapter 20 Design and Analysis of Experiments and Observational Studies (Capital One)......Page 722
  20.1 Observational Studies......Page 723
  20.2 Randomized, Comparative Experiments......Page 725
  20.3 The Four Principles of Experimental Design......Page 726
  20.4 Experimental Designs......Page 728
  20.5 Issues in Experimental Design......Page 732
  20.6 Analyzing a Design in One Factor—The One-Way Analysis of Variance......Page 734
  20.7 Assumptions and Conditions for ANOVA......Page 738
  *20.8 Multiple Comparisons......Page 741
  20.9 ANOVA on Observational Data......Page 743
  20.10 Analysis of Multifactor Designs......Page 744
  Ethics in Action......Page 754
  Technology Help: Analysis of Variance......Page 758
  Brief Case: Design a Multifactor Experiment......Page 759
 Chapter 21 Quality Control (Sony)......Page 772
  21.1 A Short History of Quality Control......Page 773
  21.2 Control Charts for Individual Observations (Run Charts)......Page 777
  21.3 Control Charts for Measurements: X and R Charts......Page 781
  21.4 Actions for Out-of-Control Processes......Page 787
  21.5 Control Charts for Attributes: p Charts and c Charts......Page 793
  21.6 Philosophies of Quality Control......Page 796
  Ethics in Action......Page 797
  Technology Help: Quality Control Charts......Page 799
  Brief Case: Laptop Touchpad Quality......Page 800
 Chapter 22 Nonparametric Methods (i4cp)......Page 808
  22.1 Ranks......Page 809
  22.2 The Wilcoxon Rank-Sum/Mann-Whitney Statistic......Page 810
  22.3 Kruskal-Wallace Test......Page 814
  22.4 Paired Data: The Wilcoxon Signed-Rank Test......Page 817
  *22.5 Friedman Test for a Randomized Block Design......Page 820
  22.6 Kendall’s Tau:Measuring Monotonicity......Page 821
  22.7 Spearman’s Rho......Page 822
  22.8 When Should You Use Nonparametric Methods?......Page 823
  Ethics in Action......Page 824
  Technology Help: Nonparametric Methods......Page 826
  Brief Case: Real Estate Reconsidered......Page 827
 Chapter 23 Decision Making and Risk (Data Description, Inc.)......Page 836
  23.1 Actions, States of Nature, and Outcomes......Page 837
  23.2 Payoff Tables and Decision Trees......Page 838
  23.3 Minimizing Loss and Maximizing Gain......Page 839
  23.4 The Expected Value of an Action......Page 840
  23.5 Expected Value with Perfect Information......Page 841
  23.6 Decisions Made with Sample Information......Page 842
  23.7 Estimating Variation......Page 844
  23.8 Sensitivity......Page 846
  23.9 Simulation......Page 847
  Ethics in Action......Page 849
  Brief Cases: Texaco-Pennzoil and Insurance Services, Revisited......Page 851
 Chapter 24 Introduction to Data Mining (Paralyzed Veterans of America)......Page 858
  24.1 The Big Data Revolution......Page 859
  24.2 Direct Marketing......Page 860
  24.3 The Goals of Data Mining......Page 862
  24.4 Data Mining Myths......Page 863
  24.5 Successful Data Mining......Page 864
  24.7 Data Mining Algorithms......Page 866
  24.8 The Data Mining Process......Page 870
  24.9 Summary......Page 872
  Ethics in Action......Page 873
  Case Study V: Marketing Experiment......Page 875
 A. Answers......Page 876
 B. Tables and Selected Formulas......Page 930
 C. Photo Acknowledgments......Page 949
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