STATISTICAL TECHNIQUES IN BUSINESS & ECONOMICS FIFTEENTH EDITIONPDF电子书下载

Chapter1 What Is Statistics？ 1

1.1 Introduction 2

1.2 Why Study Statistics？ 2

1.3 What Is Meant by Statistics？ 4

1.4 Types of Statistics 6

Descriptive Statistics 6

Inferential Statistics 6

1.5 Types of Variables 8

1.6 Levels of Measurement 9

Nominal-Level Data 10

Ordinal-Level Data 11

Interval-Level Data 11

Ratio-Level Data 12

Exercises 14

1.7 Ethics and Statistics 14

1.8 Computer Applications 14

Chapter Summary 16

Chapter Exercises 16

Data Set Exercises 19

Answers to Self-Review 20

Chapter2 Describing Data：Frequency Tables，Frequency Distributions，and Graphic Presentation 21

2.1 Introduction 22

2.2 Constructing a Frequency Table 23

Relative Class Frequencies 23

Graphic Presentation of Qualitative Data 24

Exercises 28

2.3 Constructing Frequency Distributions：Quantitative Data 29

2.4 A Software Example 34

2.5 Relative Frequency Distribution 34

Exercises 35

2.6 Graphic Presentation of a Frequency Distribution 36

Histogram 36

Frequency Polygon 38

Exercises 41

Cumulative Frequency Distributions 42

Exercises 44

Chapter Summary 46

Chapter Exercises 46

Data Set Exercises 53

Software Commands 54

Answers to Self-Review 55

Chapter3 Describing Data：Numerical Measures 57

3.1 Introduction 58

3.2 The Population Mean 58

3.3 The Sample Mean 60

3.4 Properties of the Arithmetic Mean 61

Exercises 62

3.5 The Weighted Mean 63

Exercises 64

3.6 The Median 64

3.7 The Mode 65

Exercises 67

3.8 Software Solution 69

3.9 The Relative Positions of the Mean，Median，and Mode 69

Exercises 71

3.10 The Geometric Mean 72

Exercises 73

3.11 Why Study Dispersion？ 74

3.12 Measures of Dispersion 75

Range 75

Mean Deviation 76

Exercises 79

Variance and Standard Deviation 79

Exercises 82

3.13 Software Solution 84

Exercises 84

3.14 Interpretation and Uses of the Standard Deviation 85

Chebyshev’s Theorem 85

The Empirical Rule 86

Exercises 87

3.15 The Mean and Standard Deviation of Grouped Data 88

The Arithmetic Mean 88

Standard Deviation 89

Exercises 91

3.16 Ethics and Reporting Results 92

Chapter Summary 92

Pronunciation Key 94

Chapter Exercises 94

Data Set Exercises 99

Software Commands 100

Answers to Self-Review 100

Chapter4 Describing Data：Displaying and Exploring Data 102

4.1 Introduction 103

4.2 Dot Plots 103

4.3 Stem-and-Leaf Displays 105

Exercises 109

4.4 Measures of Position 111

Quartiles，Deciles，and Percentiles 111

Exercises 115

Box Plots 116

Exercises 118

4.5 Skewness 119

Exercises 123

4.6 Describing the Relationship between Two Variables 124

Exercises 127

Chapter Summary 129

Pronunciation Key 129

Chapter Exercises 130

Data Set Exercises 135

Software Commands 135

Answers to Self-Review 136

A Review of Chapters 1-4 137

Glossary 137

Problems 139

Cases 141

Practice Test 142

Chapter5 A Survey of Probability Concepts 144

5.1 Introduction 145

5.2 What Is a Probability？ 146

5.3 Approaches to Assigning Probabilities 148

Classical Probability 148

Empirical Probability 149

Subjective Probability 150

Exercises 152

5.4 Some Rules for Computing Probabilities 153

Rules of Addition 153

Exercises 158

Rules of Multiplication 159

5.5 Contingency Tables 162

5.6 Tree Diagrams 164

Exercises 166

5.7 Bayes’ Theorem 167

Exercises 170

5.8 Principles of Counting 171

The Multiplication Formula 171

The Permutation Formula 172

The Combination Formula 174

Exercises 176

Chapter Summary 176

Pronunciation Key 177

Chapter Exercises 178

Data Set Exercises 182

Software Commands 183

Answers to Self-Review 184

Chapter6 Discrete Probability Distributions 186

6.1 Introduction 187

6.2 What Is a Probability Distribution？ 187

6.3 Random Variables 189

Discrete Random Variable 190

Continuous Random Variable 190

6.4 The Mean，Variance，and Standard Deviation of a Discrete Probability Distribution 191

Mean 191

Variance and Standard Deviation 191

Exercises 193

6.5 Binomial Probability Distribution 195

How Is a Binomial Probability Computed？ 196

Binomial Probability Tables 198

Exercises 201

Cumulative Binomial Probability Distributions 202

Exercises 203

6.6 Hypergeometric Probability Distribution 204

Exercises 207

6.7 Poisson Probability Distribution 207

Exercises 212

Chapter Summary 212

Chapter Exercises 213

Data Set Exercises 218

Software Commands 219

Answers to Self-Review 221

Chapter7 Continuous Probability Distributions 222

7.1 Introduction 223

7.2 The Family of Uniform Probability Distributions 223

Exercises 226

7.3 The Family of Normal Probability Distributions 227

7.4 The Standard Normal Probability Distribution 229

Applications of the Standard Normal Distribution 231

The Empirical Rule 231

Exercises 233

Finding Areas under the Normal Curve 233

Exercises 236

Exercises 239

Exercises 241

7.5 The Normal Approximation to the Binomial 242

Continuity Correction Factor 242

How to Apply the Correction Factor 244

Exercises 245

7.6 The Family of Exponential Distributions 246

Exercises 250

Chapter Summary 251

Chapter Exercises 252

Data Set Exercises 256

Software Commands 256

Answers to Self-Review 257

A Review of Chapters 5-7 258

Glossary 259

Problems 260

Cases 261

Practice Test 263

Chapter8 Sampling Methods and the Central Limit Theorem 265

8.1 Introduction 266

8.2 Sampling Methods 266

Reasons to Sample 266

Simple Random Sampling 267

Systematic Random Sampling 270

Stratified Random Sampling 270

Cluster Sampling 271

Exercises 272

8.3 Sampling “Error” 274

8.4 Sampling Distribution of the Sample Mean 275

Exercises 278

8.5 The Central Limit Theorem 279

Exercises 285

8.6 Using the Sampling Distribution of the Sample Mean 286

Exercises 289

Chapter Summary 289

Pronunciation Key 290

Chapter Exercises 290

Data Set Exercises 295

Software Commands 295

Answers to Self-Review 296

Chapter9 Estimation and Confidence Intervals 297

9.1 Introduction 298

9.2 Point Estimate for a Population Mean 298

9.3 Confidence Intervals for a Population Mean 299

Population Standard Deviation Known σ 300

A Computer Simulation 304

Exercises 305

Population Standard Deviationσ Unknown 306

Exercises 312

9.4 A Confidence Interval for a Proportion 313

Exercises 316

9.5 Choosing an Appropriate Sample Size 316

Sample Size to Estimate a Population Mean 317

Sample Size to Estimate a Population Proportion 318

Exercises 320

9.6 Finite-Population Correction Factor 320

Exercises 322

Chapter Summary 323

Chapter Exercises 323

Data Set Exercises 327

Software Commands 328

Answers to Self-Review 329A Review of Chapters 8 and 9 329

Glossary 330

Problems 331

Case 332

Practice Test 332

Chapter10 One-Sample Tests of Hypothesis 333

10.1 Introduction 334

10.2 What Is a Hypothesis？ 334

10.3 What Is Hypothesis Testing？ 335

10.4 Five-Step Procedure for Testing a Hypothesis 335

Step 1：State the Null Hypothesis（H0） and the Alternate Hypothesis（H1） 336

Step 2：Select a Level of Significance 337

Step 3：Select the Test Statistic 338

Step 4：Formulate the Decision Rule 338

Step 5：Make a Decision 339

10.5 One-Tailed and Two-Tailed Tests of Significance 340

10.6 Testing for a Population Mean：Known Population Standard Deviation 341

A Two-Tailed Test 341

A One-Tailed Test 345

10.7 p-Value in Hypothesis Testing 345

Exercises 347

10.8 Testing for a Population Mean：Population Standard Deviation Unknown 348

Exercises 352

A Software Solution 353

Exercises 355

10.9 Tests Concerning Proportions 356

Exercises 359

10.10 Type Ⅱ Error 359

Exercises 362

Chapter Summary 362

Pronunciation Key 363

Chapter Exercises 364

Data Set Exercises 368

Software Commands 369

Answers to Self-Review 369

Chapter11 Two-Sample Tests of Hypothesis 371

11.1 Introduction 372

11.2 Two-Sample Tests of Hypothesis：Independent Samples 372

Exercises 377

11.3 Two-Sample Tests about Proportions 378

Exercises 381

11.4 Comparing Population Means with Unknown Population Standard Deviations 382

Equal Population Standard Deviations 383

Exercises 386

Unequal Population Standard Deviations 388

Exercises 391

11.5 Two-Sample Tests of Hypothesis：Dependent Samples 392

11.6 Comparing Dependent and IndependentSamples 395

Exercises 398

Chapter Summary 399

Pronunciation Key 400

Chapter Exercises 400

Data Set Exercises 406

Software Commands 407

Answers to Self-Review 408

Chapter12 Analysis of Variance 410

12.1 Introduction 411

12.2 The F Distribution 411

12.3 Comparing Two Population Variances 412

Exercises 415

12.4 ANOVA Assumptions 416

12.5 The ANOVA Test 418

Exercises 425

12.6 Inferences about Pairs of Treatment Means 426

Exercises 429

12.7 Two-Way Analysis of Variance 430

Exercises 434

12.8 Two-Way ANOVA with Interaction 435

Interaction Plots 436

Hypothesis Test for Interaction 437

Exercises 440

Chapter Summary 442

Pronunciation Key 443

Chapter Exercises 443

Data Set Exercises 451

Software Commands 452

Answers to Self-Review 454

A Review of Chapters 10-12 455

Glossary 455

Problems 456

Cases 459

Practice Test 459

Chapter13 Correlation and Linear Regression 461

13.1 Introduction 462

13.2 What Is Correlation Analysis？ 463

13.3 The Correlation Coefficient 465

Exercises 470

13.4 Testing the Significance of the Correlation Coereicient 472

Exercises 475

13.5 Regression Analysis 476

Least Squares Principle 476

Drawing the Regression Line 479

Exercises 481

13.6 Testing the Significance of the Slope 483

Exercises 486

13.7 Evaluating a Regression Equation’s Ability to Predict 486

The Standard Error of Estimate 486

The Coefficient of Determination 487

Exercises 488

Relationships among the Correlation Coefficient，the Coefficient of Determination，and the Standard Error of Estimate 488

Exercises 490

13.8 Interval Estimates of Prediction 490

Assumptions Underlying Linear Regression 490

Constructing Confidence and Prediction Intervals 492

Exercises 494

13.9 Transforming Data 495

Exercises 497

Chapter Summary 498

Pronunciation Key 499

Chapter Exercises 500

Data Set Exercises 509

Software Commands 510

Answers to Self-Review 511

Chapter14 Multiple Regression Analysis 512

14.1 Introduction 513

14.2 Multiple Regression Analysis 513

Exercises 517

14.3 Evaluating a Multiple Regression Equation 519

The ANOVA Table 519

Multiple Standard Error of Estimate 520

Coefficient of Multiple Determination 521

Adjusted Coefficient of Determination 522

Exercises 523

14.4 Inferences in Multiple Linear Regression 523

Global Test：Testing the Multiple Regression Model 524

Evaluating Individual Regression Coefficients 526

Exercises 530

14.5 Evaluating the Assumptions of Multiple Regression 531

Linear Relationship 532

Variation in Residuals Same for Large and Small Y Values 533

Distribution of Residuals 534

Multicollinearity 534

Independent Observations 537

14.6 Qualitative Independent Variables 537

14.7 Regression Models with Interaction 540

14.8 Stepwise Regression 542

Exercises 544

14.9 Review of Multiple Regression 546

Chapter Summary 551

Pronunciation Key 553

Chapter Exercises 553

Data Set Exercises 565

Software Commands 566

Answers to Self-Review 567

A Review of Chapters 13 and 14 567

Glossary 568

Problems 569

Cases 570

Practice Test 571

Chapter15 Index Numbers 573

15.1 Introduction 574

15.2 Simple Index Numbers 574

15.3 Why Convert Data to Indexes？ 577

15.4 Construction of Index Numbers 577

Exercises 578

15.5 Unweighted Indexes 579

Simple Average of the Price Indexes 579

Simple Aggregate Index 580

15.6 Weighted Indexes 581

Laspeyres Price Index 581

Paasche Price Index 582

Fisher’s Ideal Index 584

Exercises 584

15.7 Value Index 585

Exercises 586

15.8 Special-Purpose Indexes 587

Consumer Price Index 588

Producer Price Index 589

Dow Jones Industrial Average（DJIA） 589

S＆P 500 Index 590

Exercises 591

15.9 Consumer Price Index 592

Special Uses of the Consumer Price Index 592

15.10 Shifting the Base 595

Exercises 597

Chapter Summary 598

Chapter Exercises 599

Software Commands 602

Answers to Self-Review 603

Chapter16 Time Series and Forecasting 604

16.1 Introduction 605

16.2 Components of a Time Series 605

Secular Trend 605

Cyclical Variation 606

Seasonal Variation 607

Irregular Variation 608

16.3 A Moving Average 608

16.4 Weighted Moving Average 611

Exercises 614

16.5 Linear Trend 615

16.6 Least Squares Method 616

Exercises 618

16.7 Nonlinear Trends 618

Exercises 620

16.8 Seasonal Variation 621

Determining a Seasonal Index 621

Exercises 626

16.9 Deseasonalizing Data 627

Using Deseasonalized Data to Forecast 628

Exercises 630

16.10 The Durbin-Watson Statistic 631

Exercises 636

Chapter Summary 636

Chapter Exercises 636

Data Set Exercise 643

Software Commands 643

Answers to Self-Review 644

A Review of Chapters 15 and 16 645

Glossary 646

Problems 646

Practice Test 647

Chapter17 Nonparametric Methods：Goodness-of-Fit Tests 648

17.1 Introduction 649

17.2 Goodness-of-Fit Test：Equal Expected Frequencies 649

Exercises 654

17.3 Goodness-of-Fit Test：Unequal Expected Frequencies 655

17.4 Limitations of Chi-Square 657

Exercises 659

17.5 Testing the Hypothesis That a Distribution of Data Is from a Normal Population 659

17.6 Graphical and Statistical Approaches to Confirm Normality 662

Exercises 665

17.7 Contingency Table Analysis 667

Exercises 671

Chapter Summary 672

Pronunciation Key 672

Chapter Exercises 672

Data Set Exercises 677

Software Commands 678

Answers to Self-Review 679

Chapter18 Nonparametric Methods：Analysis of Ranked Data 680

18.1 Introduction 681

18.2 The Sign Test 681

Exercises 685

Using the Normal Approximation to the Binomial 686

Exercises 688

Testing a Hypothesis about a Median 688

Exercises 689

18.3 Wilcoxon Signed-Rank Test for Dependent Samples 690

Exercises 693

18.4 Wilcoxon Rank-Sum Test for Independent Samples 695

Exercises 698

18.5 Kruskal-Wallis Test：Analysis of Variance by Ranks 698

Exercises 702

18.6 Rank-Order Correlation 704

Testing the Significance of rs 706

Exercises 707

Chapter Summary 709

Pronunciation Key 710

Chapter Exercises 710

Data Set Exercises 713

Software Commands 713

Answers to Self-Review 714

A Review of Chapters 17 and 18 716

Glossary 716

Problems 717

Cases 718

Practice Test 718

Chapter19 Statistical Process Control and Quality Management 720

19.1 Introduction 721

19.2 A Brief History of Quality Control 721

Six Sigma 724

19.3 Causes of Variation 724

19.4 Diagnostic Charts 725

Pareto Charts 725

Fishbone Diagrams 727

Exercises 728

19.5 Purpose and Types of Quality Control Charts 729

Control Charts for Variables 729

Range Charts 733

19.6 In-Control and Out-of-Control Situations 734

Exercises 736

19.7 Attribute Control Charts 737

Percent Defective Charts 737

c-Bar Charts 740

Exercises 741

19.8 Acceptance Sampling 742

Exercises 746

Chapter Summary 746

Pronunciation Key 747

Chapter Exercises 747

Software Commands 751

Answers to Self-Review 752

Appendixes 753

Appendix A：Data Sets 754

Appendix B：Tables 764

Appendix C：Answers to Odd-Numbered Chapter Exercises and Review Exercises and Solutions to Practice Tests 782

Photo Credits 829

Index 831