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