应用统计分析 使用EXCEL 英文版PDF电子书下载

1 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

11.1 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 11.1 Pepsi's Exclusivity Agreement with a University 327

CASE 11.2 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 332

12.3 Observational and Experimental Data 348

12.4 Inference about the Difference between Two Means:Matched Pairs Experiment 349

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

13 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:Randomized 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 Coefficients 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

18.1 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 IndependentVariables 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