I WHAT IS STATISTICS? 1 1.1 Introduction 2 1.2 Key Statistical Concepts 6 1.3 Statistics and the Computer 7 1.4 World Wide Web and Learning Center 7 APPENDIX 1.A: Introduction to Microsoft Excel 10 2 GRAPHICAL DESCRIPTIVE TECHNIQUES 15 2.1 Introduction 16 2.2 Types of Data 16 2.3 Graphically Describing Interval Data: Frequency Distributions and Histograms 20 2.4 Graphically Describing Nominal Data: Bar and Pie Charts 33 2.5 Describing Time-Series Data: Line Charts 38 2.6 Describing the Relationship between Two Interval Variables: Scatter Diagrams 42 2.7 Summary 49 3 NUMERICAL DESCRIPTIVE TECHNIQUES FOR INTERVAL DATA 52 3.1 Introduction 53 3.2 Measures of Central Location 54 3.3 Measures of Variability 60 3.4 Other Measures of Shape (Optional) 70 3.5 Measures of Relative Standing and Box Plots 71 3.6 Measures of Linear Relationship 76 3.7 General Guidelines for Exploring Data 84 3.8 Summary 85 4 PROBABILITY 89 4.1 Introduction 90 4.2 Assigning Probability to Events 90 4.3 Joint, Marginal, and Conditional Probability 95 4.4 Probability Rules and Trees 103 4.5 Summary 113 CASE 4.1 Let's Make a Deal 116 CASE 4.2 To Bunt or Not to Bunt, That Is the Question 116 5 RANDOM VARIABLES AND DISCRETE PROBABILITY DISTRIBUTIONS 118 5.1 Introduction 119 5.2 Random Variables and Probability Distributions 119 5.3 Describing the Population/Probability Distribution 124 5.4 Binomial Distribution 128 5.5 Poisson Distribution 136 5.6 Summary 141 CASE 5.1 To Bunt or Not to Bunt, That Is the Question, Part II 145 6 CONTINUOUS PROBABILITY DISTRIBUTIONS 146 6.1 Introduction 147 6.2 Probability Density Functions 147 6.3 Normal Distribution 153 6.4 Other Continuous Distributions 170 6.5 Summary 187 7 SAMPLING AND SAMPLING PLANS 188 7.1 Introduction 189 7.2 Sampling 189 7.3 Sampling Plans 191 7.4 Errors Involved in Sampling 196 7.5 Summary 198 8 SAMPLING DISTRIBUTIONS 199 8.1 Introduction 200 8.2 Sampling Distribution of the Mean 200 8.3 Creating the Sampling Distribution by Computer Simulation (Optional) 212 8.4 Sampling Distribution of a Proportion 215 8.5 Sampling Distribution of the Difference between Two Means 220 8.6 From Here to Inference 223 8.7 Summary 224 9 INTRODUCTION TO ESTIMATION 227 9.1 Introduction 228 9.2 Concepts of Estimation 228 9.3 Estimating the Population Mean when the Population Standard Deviation Is Known 232 9.4 Selecting the Sample Size 245 9.5 Simulation Experiments (Optional) 247 9.6 Summary 250 10 INTRODUCTION TO HYPOTHESIS TESTING 253 10.1 Introduction 254 10.2 Concepts of Hypothesis Testing 255 10.3 Testing the Population Mean when the Population Standard Deviation Is Known 257 10.4 Calculating the Probability of a Type II Error 279 10.5 The Road Ahead 288 10.6 Summary 291 11 INFERENCE ABOUT A SINGLE POPULATION 293 1 l. 1 Introduction 294 11.2 Inference about a Population Mean when the Standard Deviation Is Unknown 295 11.3 Inference about a Population Variance 305 11.4 Inference about a Population Proportion 311 11.5 Summary 323 CASE l l.1 Pepsi's Exclusivity Agreement with a University 327 CASE I 1.2 Pepsi's Exclusivity Agreement with a University: The Coke Side of the Equation 328 CASE 11.3 Number of Uninsured Motorists 328 12 INFERENCE ABOUT TWO POPULATIONS 330 12.1 Introduction 331 12.2 Inference about the Difference between Two Means: Independent Samples 33: 12.3 Observational and Experimental Data 348 12.4 Inference about the Difference betweenTwo Means: Matched Pairs Experiment 12.5 Inference about the Ratio of Two Variances 361 12.6 Inference about the Difference between Two Population Proportions 367 12.7 Summary 378 CASE 12.1 Bonanza International 386 CASE 12.2 Accounting Course Exemptions 387 113 STATISTICAL INFERENCE: REVIEW OF CHAPTERS 11 AND 12 388 13.1 Introduction 389 13.2 Guide to Identifying the Correct Technique: Chapters 11 and 12 389 CASE 13.1 Quebec Separation: Oui ou non? 403 CASE 13.2 Host Selling and Announcer Commercials 403 14 ANALYSIS OF VARIANCE 405 14.1 Introduction 406 14.2 Single-Factor (One-Way) Analysis of Variance: Independent Samples 407 14.3 Analysis of Variance Experimental Designs 423 14.4 Single-Factor Analysis of Variance: Randqmized Blocks 425 14.5 Two-Factor Analysis of Variance: Independent Samples 434 14.6 Multiple Comparisons 449 14.7 Bartlett's Test 455 14.8 Summary 457 15 CHI-SQUARED TESTS 464 15.1 Introduction 465 15.2 Chi-Squared Goodness-of-Fit Test 465 15.3 Chi-Squared Test of a Contingency Table 472 15.4 Summary of Tests on Nominal Data 482 15.5 Chi-Squared Test for Normality 484 15.6 Summary 489 CASE 15.1 Predicting the Outcomes of Basketball, Baseball, Football, and Hockey Games from Intermediate Results 493 CASE 15.2 Can Exposure to a Code of Professional Ethics Help Make Managers More Ethical? 494 16 NONPARAMETRIC STATISTICAL TECHNIQUES 496 16.1 Introduction 497 16.2 Wilcoxon Rank Sum Test 499 16.3 Sign Test and Wilcoxon Signed Rank Sum Test 511 16.4 Kruskal-WallisTest 524 16.5 Friedman Test 529 16.6 Summary 535 17 SIMPLE LINEAR REGRESSION AND CORRELATION 542 17.1 Introduction 543 17.2 Model 544 17.3 Estimating the Cdefficients 546 17.4 Error Variable: Required Conditions 552 17.5 Assessing the Model 555 17.6 Using the Regression Equation 564 17.7 Coefficients of Correlation 568 17.8 Regression Diagnostics I 574 17.9 Summary 580 CASE 17.1 Predicting University Grades from High School Grades 585 CASE 17.2 Insurance Compensation for Lost Revenues 586 18 MULTIPLE REGRESSION 588 18. I Introduction 589 18.2 Model and Required Conditions 589 18.3 Estimating the Coefficients and Assessing the Model 590 18.4 Regression Diagnostics II 605 18.5 Regression Diagnostics III (Time Series) 612 18.6 Nominal Independent Variables 623 18.7 Summary 630 CASE 18.1 Quebec Referendum Vote: Was There Electoral Fraud? 634 CASE 18.2 Quebec Referendum Vote: The Rebuttal 635 19 STATISTICAL INFERENCE: CONCLUSION 636 19.1 Introduction 637 19.2 Identifying the Correct Technique: Summary of Statistical Inference 637 CASE 19.1 Do Banks Discriminate against Women Business Owners? I 644 CASE 19.2 Do Banks Discriminate against Women Business Owners? II 647 19.3 The Last Word 653 CASE 19.3 Ambulance and Fire Department Response Interval Study 665 CASE 19.4 PC Magazine Survey 666 CASE 19.5 WLU Graduate Survey 667 CASE 19.6 Evaluation of a New Antidepressant Drug 668 CASE 19.7 Nutrition Education Programs 669 CASE 19.8 Do Banks Discriminate against Women Business Owners? III 670 Appendix A Sample Statistics from Data Files in Chapters 9 and 10 A-1 AppendixB Tables B-1 Appendix C Answers to Selected Even-Numbered Exercises C-1 Index I-1
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