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CONTENTS 1

Chapter 1 1

DATA AND STATISTICS 1

Statistics in Practice:Fisons Corporation 2

Statistics in Practice:Nevada Occupational Health Clinic 2

Statistics in Practice:Business Week 2

1.1 Applications in Business and Economics 3

1.2 Data 5

1.3 Data Sources 7

1.4 Descriptive Statistics 10

1.5 Statistical Inference and Probability 12

Chapter 2 20

DESCRIPTTVE STATISTICS I: TABULAR AND GRAPHICAL METHODS 20

Statistics in Practice:Colgate-Palmolive Company 21

2.1 Summarizing Qualitative Data 22

2.2 Summarizing Quantitative Data 27

2.3 The Role of the Computer 36

2.4 Exploratory Data Analysis 38

2.5 Crosstabulations and Scatter Diagrams 43

Chapter 3 62

DESCRIPTTVE STATISTICSⅡ: NUMERICAL METHODS 62

Statistics in Practice:Barnes Hospital 63

3.1 Measures of Location 64

3.2 Measures of Dispersion 73

3.3 Some Uses of the Mean and the Standard Deviation 79

3.4 Exploratory Data Analysis 85

3.5 Measures of Association between Two Variables 89

3.6 The Role of the Computer 97

3.7 Computing Measures of Location and Dispersion for Grouped Data 99

Chapter 4 116

5.2 Discrete Probability Distributions 116

INTRODUCTION TO PROBABILITY 116

Statistics in Practice:Morton International 117

4.1 Experiments, the Sample Space, and Counting Rules 118

4.2 Assiging Probabilities to Experimental Outcomes 124

4.3 Events and Their Probabilities 129

4.4 Some Basic Relationships of Probability 131

4.5 Conditional Probability 138

4.6 Bayes' Theorem 146

Chapter 5 161

DISCRETE PROBABILITY DISTRIBUTIONS 161

Statistics in Practice:Xerox Corporation 162

5.1 Random Variables 163

5.3 Expected Value and Variance 169

5.4 The Binomial Probability Distribution 172

5.5 The Poisson Probability Distribution 183

5.6 The Hypergeometric Probability Distribution 187

Chapter 6 197

CONT■ ■ DISTRIBUTIONS 197

Statistics in Practice:Procter Gamble 198

6.1 The Uniform Probability Distribution 199

6.2 The Normal Probability Distribution 204

6.3 Normal Approximation of Binomial Probabilities 216

6.4 The Exponential Probability Distribution 219

Statistics in Practice:Mead Corporation 231

SAM■ ■ DISTRIBUTIONS 231

Chapter 7 231

7.1 The Electronics Associates Sampling Problem 233

7.2 Simple Random Sampling 234

7.3 Point Estimation 239

7.4 Introduction to Sampling Distributions 242

7.5 Sampling Distribution of ■ 246

7.6 Sampling Distribution of ■ 257

7.7 Properties of Point Estimators 262

7.8 Other Sampling Methods 265

INTERYAL ESTIMATION 276

Chapter 8 276

Statistics in Practice:Dollar General Corporation 277

8.1 Interval Estimation of Population Mean: Large-Sample Case 278

8.2 Interval Estimation of a Population Mean: Small-Sample Case 287

8.3 Determining the Sample Size 294

8.4 Interval Estimation of a Population Proportion 297

Chapter 9 313

HYPOTHESIS TESTING 313

Statistics in Practice:Harris Corporation 314

9.1 Developing Null and Alternative Hypotheses 315

9.2 Type Ⅰ and Type Ⅱ Errors 318

9.3 One-Tailed Tests About a Population Mean: Large-Sample Case 320

9.4 Two-Tailed TestS About a Population Mean: Large-Sample CaSe 330

9.5 Tests about a Population Mean: Small-Sample Case 337

9.6 Tests about a Population Proportion 342

9.7 Hypothesis Testing and Decision Making 348

9.8 Calculating the Probability of Type Ⅱ Errors 349

9.9 Determining the Sample Size for a Hypothesis Test About a Population Mean 354

Chapter 10 366

STATISTICAL INFERENCE ABORT MEANS AND PROPORTIONS WITH TWO POPULATIONS 366

10.1 Estimation of the Difference between the Means of Two Populations: Independent Samples 368

10.2 Hypothesis Tests about the Difference between the Means of Two Populations: Independent Samples 377

10.3 Inferences about the Difference between the Means of Two Populations:Matched Samples 385

10.4 Inferences about the Difference between the Proportions of Two Populations 390

Chapter 11 402

INFERENCES ABOUT POPULATION VARIANCES 402

Statistics in Practice:U.S. General Accounting Office 403

11.1 Inferences about a Population Variance 404

11.2 Inferences about the Variances of Two Populations 413

Chapter 12 424

TESTS OF GOODNESS OF FIT AND INDEPENDENCE 424

Statistics in Practice:United Way 425

12.1 Goodness Of Fit Test: A Multinomial Population 426

12.2 Test of Independence: Contingency Tables 430

12.3 Goodness of Fit Test: Poisson and Normal Distributions 437

Chapter 13 450

ANALYSIS OF VARIANCE AND EXPERIMENTAL DESIGN 450

Statistics in Practice:Bruke Marketing Services,Inc. 451

13.1 An Introduction to Analysis of Variance 452

13.2 Analysis of Variance: Testing for the Equality of k Population Means 456

13.3 Multiple Comparison Procedures 465

13.4 An Introduction to Experimental Design 469

13.5 Completely Randomized Designs 472

13.6 Randomized Block Design 478

13.7 Factorial Experiments 484

Chapter 14 506

SIMPLE LINEAR REGRESSION 506

Statistics in Practice:Polaroid Corporation 507

14.1 The Simple Linear Regression Model 508

14.2 The Least Squares Method 510

14.3 The Coefficient of Determination 519

14.4 Model Assumptions 527

14.5 Testing for significance 529

14.6 Using the Estimated Regression Equation for Estimation and Prediction 537

14.7 Computer Solution of Regression Problems 543

14.8 Residual Analysis: Testing Model Assumptions 547

14.9 Residual Analysis: Outliers and Influential Observations 556

MULTIPLE REGRESSION 577

Chapter 15 577

Statistics in Practice:Mead Corporation 578

15.1 The Multiple Regression Model 579

15.2 The Least Squares Method 580

15.3 The Multiple Coefficient of Determination 588

15.4 Model Assumptions 591

15.5 Testing for Significance 593

15.6 Using the Estimated Regression Equation for Estimation and Prediction 600

15.7 Qualitative Independent Variables 602

15.8 Residual Analysis 610

Chapter 16 630

REGRESSION ANALYSIS: MODEL BUILDING 630

Statistics in Practice:Monsanto Company 631

16.1 The General Linear Model 632

16.2 DetErmining when to Add or Delete Variables 646

16.3 First Steps in the Analysis of a Larger Problem 651

16.4 Variable-Selection Procedures 655

16.6 Multiple Regression Approach to Analysis of Variance and Experimental Design 670

Chapter 17 680

INDEX NUMBERS 680

Statistics in Practice:U.S. Department of Labor,Bureau of Labor Statistics 681

17.2 AggregatE Price Indexes 682

17.1 Price Relatives 682

17.3 Computing an Aggregate Index from Price Relatives 686

17.4 Some Important Price Indexes 688

17.5 Deflating a Series by Price Indexes 690

17.6 Price Indexes: Other Considerations 693

17.7 Quantity Indexes 694

Chapter 18 699

FORECASTING 699

18.1 The Components of a Time Series 701

18.2 Using Smoothing Methods in Forecasting 705

18.3 Using Trend Projection in Forecasting 715

18.4 Using Trend and Seasonal Components in Forecasting 721

18.5 Using Regression Analysis in Forecasting 731

18.6 Qualitative Approaches to Forecasting 733

Chapter 19 744

NONPARAMETRIC METHODS 744

Statistics in Practice:West Shell Realtors 745

19.1 Sign Test 746

19.2 Wilcoxon Signed-Rank Test 753

19.3 Mann-Whitney-Wilcoxon Test 758

19.5 Kruskal-Wallis Test 766

19.5 Rank Correlation 769

STATISTICAL METHODS FOR QUALITY CONTROL 779

Chapter 20 779

Statistics in Practice:Dow Chemical U.S.A. 780

20.1 Statistical Process Control 781

20.2 Acceptance Sampling 795

Chapter 21 809

SAMPLE SURVEY 809

Statistics in Practice:Cincinnati Gas Electric Company 809

21.1 Terminology Used in Sample Surveys 810

21.2 Types of Surveys and Sampling Methods 811

21.3 Survey Errors 813

21.4 Simple Random Sampling 814

21.5 Stratified Simple Random Sampling 821

21.6 Cluster Sampling 830

21.7 Systematic Sampling 837

Chapter 22 846

DECISION ANALYSIS 846

Statistics in Practice:Ohio Edison Company 847

22.1 Structuring the Decision Problem 848

22.2 Decision Making with Probabilities 851

22.3 Expected Value of Perfect Information 855

22.4 Decision Analysis with Sample Information 858

22.3 Developing a Decision Strategy 860

22.6 Expected Value of Sample Information 866

Appendixes A-1 878