STATISTICAL TECHNIQUES IN BUSINESS & ECONOMICS FIFTEENTH EDITION2025|PDF|Epub|mobi|kindle电子书版本百度云盘下载

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Chapter1 What Is Statistics？1

1.1 Introduction2

1.2 Why Study Statistics？2

1.3 What Is Meant by Statistics？4

1.4 Types of Statistics6

Descriptive Statistics6

Inferential Statistics6

1.5 Types of Variables8

1.6 Levels of Measurement9

Nominal-Level Data10

Ordinal-Level Data11

Interval-Level Data11

Ratio-Level Data12

Exercises14

1.7 Ethics and Statistics14

1.8 Computer Applications14

Chapter Summary16

Chapter Exercises16

Data Set Exercises19

Answers to Self-Review20

Chapter2 Describing Data：Frequency Tables，Frequency Distributions，and Graphic Presentation21

2.1 Introduction22

2.2 Constructing a Frequency Table23

Relative Class Frequencies23

Graphic Presentation of Qualitative Data24

Exercises28

2.3 Constructing Frequency Distributions：Quantitative Data29

2.4 A Software Example34

2.5 Relative Frequency Distribution34

Exercises35

2.6 Graphic Presentation of a Frequency Distribution36

Histogram36

Frequency Polygon38

Exercises41

Cumulative Frequency Distributions42

Exercises44

Chapter Summary46

Chapter Exercises46

Data Set Exercises53

Software Commands54

Answers to Self-Review55

Chapter3 Describing Data：Numerical Measures57

3.1 Introduction58

3.2 The Population Mean58

3.3 The Sample Mean60

3.4 Properties of the Arithmetic Mean61

Exercises62

3.5 The Weighted Mean63

Exercises64

3.6 The Median64

3.7 The Mode65

Exercises67

3.8 Software Solution69

3.9 The Relative Positions of the Mean，Median，and Mode69

Exercises71

3.10 The Geometric Mean72

Exercises73

3.11 Why Study Dispersion？74

3.12 Measures of Dispersion75

Range75

Mean Deviation76

Exercises79

Variance and Standard Deviation79

Exercises82

3.13 Software Solution84

Exercises84

3.14 Interpretation and Uses of the Standard Deviation85

Chebyshev’s Theorem85

The Empirical Rule86

Exercises87

3.15 The Mean and Standard Deviation of Grouped Data88

The Arithmetic Mean88

Standard Deviation89

Exercises91

3.16 Ethics and Reporting Results92

Chapter Summary92

Pronunciation Key94

Chapter Exercises94

Data Set Exercises99

Software Commands100

Answers to Self-Review100

Chapter4 Describing Data：Displaying and Exploring Data102

4.1 Introduction103

4.2 Dot Plots103

4.3 Stem-and-Leaf Displays105

Exercises109

4.4 Measures of Position111

Quartiles，Deciles，and Percentiles111

Exercises115

Box Plots116

Exercises118

4.5 Skewness119

Exercises123

4.6 Describing the Relationship between Two Variables124

Exercises127

Chapter Summary129

Pronunciation Key129

Chapter Exercises130

Data Set Exercises135

Software Commands135

Answers to Self-Review136

A Review of Chapters 1-4137

Glossary137

Problems139

Cases141

Practice Test142

Chapter5 A Survey of Probability Concepts144

5.1 Introduction145

5.2 What Is a Probability？146

5.3 Approaches to Assigning Probabilities148

Classical Probability148

Empirical Probability149

Subjective Probability150

Exercises152

5.4 Some Rules for Computing Probabilities153

Rules of Addition153

Exercises158

Rules of Multiplication159

5.5 Contingency Tables162

5.6 Tree Diagrams164

Exercises166

5.7 Bayes’ Theorem167

Exercises170

5.8 Principles of Counting171

The Multiplication Formula171

The Permutation Formula172

The Combination Formula174

Exercises176

Chapter Summary176

Pronunciation Key177

Chapter Exercises178

Data Set Exercises182

Software Commands183

Answers to Self-Review184

Chapter6 Discrete Probability Distributions186

6.1 Introduction187

6.2 What Is a Probability Distribution？187

6.3 Random Variables189

Discrete Random Variable190

Continuous Random Variable190

6.4 The Mean，Variance，and Standard Deviation of a Discrete Probability Distribution191

Mean191

Variance and Standard Deviation191

Exercises193

6.5 Binomial Probability Distribution195

How Is a Binomial Probability Computed？196

Binomial Probability Tables198

Exercises201

Cumulative Binomial Probability Distributions202

Exercises203

6.6 Hypergeometric Probability Distribution204

Exercises207

6.7 Poisson Probability Distribution207

Exercises212

Chapter Summary212

Chapter Exercises213

Data Set Exercises218

Software Commands219

Answers to Self-Review221

Chapter7 Continuous Probability Distributions222

7.1 Introduction223

7.2 The Family of Uniform Probability Distributions223

Exercises226

7.3 The Family of Normal Probability Distributions227

7.4 The Standard Normal Probability Distribution229

Applications of the Standard Normal Distribution231

The Empirical Rule231

Exercises233

Finding Areas under the Normal Curve233

Exercises236

Exercises239

Exercises241

7.5 The Normal Approximation to the Binomial242

Continuity Correction Factor242

How to Apply the Correction Factor244

Exercises245

7.6 The Family of Exponential Distributions246

Exercises250

Chapter Summary251

Chapter Exercises252

Data Set Exercises256

Software Commands256

Answers to Self-Review257

A Review of Chapters 5-7258

Glossary259

Problems260

Cases261

Practice Test263

Chapter8 Sampling Methods and the Central Limit Theorem265

8.1 Introduction266

8.2 Sampling Methods266

Reasons to Sample266

Simple Random Sampling267

Systematic Random Sampling270

Stratified Random Sampling270

Cluster Sampling271

Exercises272

8.3 Sampling “Error”274

8.4 Sampling Distribution of the Sample Mean275

Exercises278

8.5 The Central Limit Theorem279

Exercises285

8.6 Using the Sampling Distribution of the Sample Mean286

Exercises289

Chapter Summary289

Pronunciation Key290

Chapter Exercises290

Data Set Exercises295

Software Commands295

Answers to Self-Review296

Chapter9 Estimation and Confidence Intervals297

9.1 Introduction298

9.2 Point Estimate for a Population Mean298

9.3 Confidence Intervals for a Population Mean299

Population Standard Deviation Known σ300

A Computer Simulation304

Exercises305

Population Standard Deviationσ Unknown306

Exercises312

9.4 A Confidence Interval for a Proportion313

Exercises316

9.5 Choosing an Appropriate Sample Size316

Sample Size to Estimate a Population Mean317

Sample Size to Estimate a Population Proportion318

Exercises320

9.6 Finite-Population Correction Factor320

Exercises322

Chapter Summary323

Chapter Exercises323

Data Set Exercises327

Software Commands328

Answers to Self-Review 329A Review of Chapters 8 and 9329

Glossary330

Problems331

Case332

Practice Test332

Chapter10 One-Sample Tests of Hypothesis333

10.1 Introduction334

10.2 What Is a Hypothesis？334

10.3 What Is Hypothesis Testing？335

10.4 Five-Step Procedure for Testing a Hypothesis335

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

Step 2：Select a Level of Significance337

Step 3：Select the Test Statistic338

Step 4：Formulate the Decision Rule338

Step 5：Make a Decision339

10.5 One-Tailed and Two-Tailed Tests of Significance340

10.6 Testing for a Population Mean：Known Population Standard Deviation341

A Two-Tailed Test341

A One-Tailed Test345

10.7 p-Value in Hypothesis Testing345

Exercises347

10.8 Testing for a Population Mean：Population Standard Deviation Unknown348

Exercises352

A Software Solution353

Exercises355

10.9 Tests Concerning Proportions356

Exercises359

10.10 Type Ⅱ Error359

Exercises362

Chapter Summary362

Pronunciation Key363

Chapter Exercises364

Data Set Exercises368

Software Commands369

Answers to Self-Review369

Chapter11 Two-Sample Tests of Hypothesis371

11.1 Introduction372

11.2 Two-Sample Tests of Hypothesis：Independent Samples372

Exercises377

11.3 Two-Sample Tests about Proportions378

Exercises381

11.4 Comparing Population Means with Unknown Population Standard Deviations382

Equal Population Standard Deviations383

Exercises386

Unequal Population Standard Deviations388

Exercises391

11.5 Two-Sample Tests of Hypothesis：Dependent Samples392

11.6 Comparing Dependent and IndependentSamples395

Exercises398

Chapter Summary399

Pronunciation Key400

Chapter Exercises400

Data Set Exercises406

Software Commands407

Answers to Self-Review408

Chapter12 Analysis of Variance410

12.1 Introduction411

12.2 The F Distribution411

12.3 Comparing Two Population Variances412

Exercises415

12.4 ANOVA Assumptions416

12.5 The ANOVA Test418

Exercises425

12.6 Inferences about Pairs of Treatment Means426

Exercises429

12.7 Two-Way Analysis of Variance430

Exercises434

12.8 Two-Way ANOVA with Interaction435

Interaction Plots436

Hypothesis Test for Interaction437

Exercises440

Chapter Summary442

Pronunciation Key443

Chapter Exercises443

Data Set Exercises451

Software Commands452

Answers to Self-Review454

A Review of Chapters 10-12455

Glossary455

Problems456

Cases459

Practice Test459

Chapter13 Correlation and Linear Regression461

13.1 Introduction462

13.2 What Is Correlation Analysis？463

13.3 The Correlation Coefficient465

Exercises470

13.4 Testing the Significance of the Correlation Coereicient472

Exercises475

13.5 Regression Analysis476

Least Squares Principle476

Drawing the Regression Line479

Exercises481

13.6 Testing the Significance of the Slope483

Exercises486

13.7 Evaluating a Regression Equation’s Ability to Predict486

The Standard Error of Estimate486

The Coefficient of Determination487

Exercises488

Relationships among the Correlation Coefficient，the Coefficient of Determination，and the Standard Error of Estimate488

Exercises490

13.8 Interval Estimates of Prediction490

Assumptions Underlying Linear Regression490

Constructing Confidence and Prediction Intervals492

Exercises494

13.9 Transforming Data495

Exercises497

Chapter Summary498

Pronunciation Key499

Chapter Exercises500

Data Set Exercises509

Software Commands510

Answers to Self-Review511

Chapter14 Multiple Regression Analysis512

14.1 Introduction513

14.2 Multiple Regression Analysis513

Exercises517

14.3 Evaluating a Multiple Regression Equation519

The ANOVA Table519

Multiple Standard Error of Estimate520

Coefficient of Multiple Determination521

Adjusted Coefficient of Determination522

Exercises523

14.4 Inferences in Multiple Linear Regression523

Global Test：Testing the Multiple Regression Model524

Evaluating Individual Regression Coefficients526

Exercises530

14.5 Evaluating the Assumptions of Multiple Regression531

Linear Relationship532

Variation in Residuals Same for Large and Small Y Values533

Distribution of Residuals534

Multicollinearity534

Independent Observations537

14.6 Qualitative Independent Variables537

14.7 Regression Models with Interaction540

14.8 Stepwise Regression542

Exercises544

14.9 Review of Multiple Regression546

Chapter Summary551

Pronunciation Key553

Chapter Exercises553

Data Set Exercises565

Software Commands566

Answers to Self-Review567

A Review of Chapters 13 and 14567

Glossary568

Problems569

Cases570

Practice Test571

Chapter15 Index Numbers573

15.1 Introduction574

15.2 Simple Index Numbers574

15.3 Why Convert Data to Indexes？577

15.4 Construction of Index Numbers577

Exercises578

15.5 Unweighted Indexes579

Simple Average of the Price Indexes579

Simple Aggregate Index580

15.6 Weighted Indexes581

Laspeyres Price Index581

Paasche Price Index582

Fisher’s Ideal Index584

Exercises584

15.7 Value Index585

Exercises586

15.8 Special-Purpose Indexes587

Consumer Price Index588

Producer Price Index589

Dow Jones Industrial Average（DJIA）589

S＆P 500 Index590

Exercises591

15.9 Consumer Price Index592

Special Uses of the Consumer Price Index592

15.10 Shifting the Base595

Exercises597

Chapter Summary598

Chapter Exercises599

Software Commands602

Answers to Self-Review603

Chapter16 Time Series and Forecasting604

16.1 Introduction605

16.2 Components of a Time Series605

Secular Trend605

Cyclical Variation606

Seasonal Variation607

Irregular Variation608

16.3 A Moving Average608

16.4 Weighted Moving Average611

Exercises614

16.5 Linear Trend615

16.6 Least Squares Method616

Exercises618

16.7 Nonlinear Trends618

Exercises620

16.8 Seasonal Variation621

Determining a Seasonal Index621

Exercises626

16.9 Deseasonalizing Data627

Using Deseasonalized Data to Forecast628

Exercises630

16.10 The Durbin-Watson Statistic631

Exercises636

Chapter Summary636

Chapter Exercises636

Data Set Exercise643

Software Commands643

Answers to Self-Review644

A Review of Chapters 15 and 16645

Glossary646

Problems646

Practice Test647

Chapter17 Nonparametric Methods：Goodness-of-Fit Tests648

17.1 Introduction649

17.2 Goodness-of-Fit Test：Equal Expected Frequencies649

Exercises654

17.3 Goodness-of-Fit Test：Unequal Expected Frequencies655

17.4 Limitations of Chi-Square657

Exercises659

17.5 Testing the Hypothesis That a Distribution of Data Is from a Normal Population659

17.6 Graphical and Statistical Approaches to Confirm Normality662

Exercises665

17.7 Contingency Table Analysis667

Exercises671

Chapter Summary672

Pronunciation Key672

Chapter Exercises672

Data Set Exercises677

Software Commands678

Answers to Self-Review679

Chapter18 Nonparametric Methods：Analysis of Ranked Data680

18.1 Introduction681

18.2 The Sign Test681

Exercises685

Using the Normal Approximation to the Binomial686

Exercises688

Testing a Hypothesis about a Median688

Exercises689

18.3 Wilcoxon Signed-Rank Test for Dependent Samples690

Exercises693

18.4 Wilcoxon Rank-Sum Test for Independent Samples695

Exercises698

18.5 Kruskal-Wallis Test：Analysis of Variance by Ranks698

Exercises702

18.6 Rank-Order Correlation704

Testing the Significance of rs706

Exercises707

Chapter Summary709

Pronunciation Key710

Chapter Exercises710

Data Set Exercises713

Software Commands713

Answers to Self-Review714

A Review of Chapters 17 and 18716

Glossary716

Problems717

Cases718

Practice Test718

Chapter19 Statistical Process Control and Quality Management720

19.1 Introduction721

19.2 A Brief History of Quality Control721

Six Sigma724

19.3 Causes of Variation724

19.4 Diagnostic Charts725

Pareto Charts725

Fishbone Diagrams727

Exercises728

19.5 Purpose and Types of Quality Control Charts729

Control Charts for Variables729

Range Charts733

19.6 In-Control and Out-of-Control Situations734

Exercises736

19.7 Attribute Control Charts737

Percent Defective Charts737

c-Bar Charts740

Exercises741

19.8 Acceptance Sampling742

Exercises746

Chapter Summary746

Pronunciation Key747

Chapter Exercises747

Software Commands751

Answers to Self-Review752

Appendixes753

Appendix A：Data Sets754

Appendix B：Tables764

Appendix C：Answers to Odd-Numbered Chapter Exercises and Review Exercises and Solutions to Practice Tests782

Photo Credits829

Index831