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Note: Contents data are machine generated based on pre-publication provided by the publisher. Contents may have variations from the printed book or be incomplete or contain other coding. ```Contents
Chapter
1 What Is Statistics? 1
Introduction 2
Why Study Statistics? 2
What Is Meant by Statistics? 4
Types of Statistics 6
Descriptive Statistics 6
Inferential Statistics 7
Types of Variables 8
Levels of Measurement 9
Nominal-Level Data 10
Ordinal-Level Data 11
Interval-Level Data 12
Ratio-Level Data 12
Exercises 14
Statistics, Graphics, and Ethics 14
Association Does Not Necessarily
Imply Causation 15
Become a Better Consumer and
a Better Producer of Information 17
Ethics 17
Computer Applications 17
Chapter Outline 19
Chapter Exercises 19
exercises.com 20
Dataset Exercises 20
Chapter
2 Describing Data: Frequency
Distributions and Graphic
Presentation 23
Introduction 24
Constructing a Frequency Distribution 25
Class Intervals and Class Midpoints 29
A Software Example 29
Relative Frequency Distribution 30
Exercises 30
Graphic Presentation of a
Frequency Distribution 31
Histogram 32
Frequency Polygon 33
Exercises 36
Cumulative Frequency Distributions 37
Exercises 40
Other Graphic Presentations of Data 41
Line Graphs 41
Bar Charts 42
Pie Charts 43
Exercises 45
Chapter Outline 46
Chapter Exercises 47
exercises.com 51
Dataset Exercises 52
Software Commands 53
Chapter
3 Describing Data: Numerical
Measures 55
Introduction 56
The Population Mean 57
The Sample Mean 58
Properties of the Arithmetic Mean 59
Exercises 60
The Weighted Mean 61
Exercises 62
The Median 62
The Mode 63
Exercises 65
Software Solution 66
The Relative Positions of the Mean, Median, and
Mode 66
Exercises 68
The Geometric Mean 69
Exercises 70
Why Study Dispersion? 71
Measures of Dispersion 72
Range 72
Mean Deviation 73
Exercises 74
Variance and Standard Deviation 74
Exercises 76
Software Solution 78
Exercises 78
Interpretation and Uses of
the Standard Deviation 79
Chebyshev?s Theorem 79
The Empirical Rule 80
Exercises 81
The Mean and Standard Deviation of Grouped
Data 81
The Arithmetic Mean 82
Standard Deviation 83
Exercises 84
Chapter Outline 85
Pronunciation Key 87
Chapter Exercises 87
exercises.com 90
Dataset Exercises 92
Software Commands 92
Chapter
4 Describing Data: Displaying and
Exploring Data 96
Introduction 97
Dot Plots 97
Stem-and-Leaf Displays 98
Exercises 103
Other Measures of Dispersion 104
Quartiles, Deciles, and Percentiles 105
Exercises 108
Box Plots 108
Exercises 111
Relative Dispersion 112
Exercises 113
Skewness 114
Exercises 117
Describing the Relationship between Two
Variables 118
Exercises 121
Chapter Outline 122
Pronunciation Key 123
Chapter Exercises 123
exercises.com 128
Dataset Exercises 128
Software Commands 129
A Review of Chapters 1?4 132
Glossary 132
Exercises 133
Cases 137
Chapter
5 A Survey of Probability
Concepts 139
Introduction 140
What Is a Probability? 141
Approaches to Assigning Probabilities 143
Classical Probability 143
Empirical Probability 144
Subjective Probability 145
Exercises 146
Some Rules for Computing Probabilities 147
Exercises 152
Rules of Multiplication 153
Contingency Tables 155
Tree Diagrams 158
Exercises 159
Bayes? Theorem 160
Exercises 164
Principles of Counting 165
The Multiplication Formula 165
The Permutation Formula 166
The Combination Formula 168
Exercises 170
Chapter Outline 170
Pronunciation Key 171
Chapter Exercises 171
exercises.com 176
Dataset Exercises 176
Software Commands 177
Chapter
6 Discrete Probability
Distributions 180
Introduction 181
What Is a Probability Distribution? 181
Random Variables 183
Discrete Random Variable 184
Continuous Random Variable 184
The Mean, Variance, and Standard Deviation of a
Probability Distribution 184
Mean 184
Variance and Standard Deviation 185
Exercises 187
Binomial Probability Distribution 188
How Is a Binomial Probability Distribution
Computed? 189
Binomial Probability Tables 191
Exercises 195
Cumulative Binomial Probability
Distributions 195
Exercises 197
Hypergeometric Probability Distribution 197
Exercises 200
Poisson Probability Distribution 201
Exercises 203
Chapter Outline 204
Chapter Exercises 205
Dataset Exercises 209
Software Commands 209
Chapter
7 Continuous Probability
Distributions 212
Introduction 213
The Family of Uniform Distribution 213
Exercises 216
The Family of Normal Probability
Distributions 217
The Standard Normal Distribution 219
Applications of the Standard Normal
Distribution 221
The Empirical Rule 222
Exercises 223
Finding Areas under the Normal Curve 224
Exercises 226
Exercises 229
Exercises 231
The Normal Approximation to the
Binomial 231
Continuity Correction Factor 232
How to Apply the Correction Factor 234
Exercises 235
Chapter Outline 236
Chapter Exercises 237
Dataset Exercises 240
Software Commands 241
A Review of Chapters 5?7 243
Glossary 243
Exercises 245
Cases 247
Chapter
8 Sampling Methods and the
Central Limit Theorem 250
Introduction 251
Sampling Methods 251
Reasons to Sample 251
Simple Random Sampling 252
Systematic Random Sampling 253
Stratified Random Sampling 254
Cluster Sampling 255
Exercises 256
Sampling ?Error? 258
Sampling Distribution of the Sample Mean 259
Exercises 262
The Central Limit Theorem 263
Exercises 269
Using the Sampling Distribution of the Sample
Mean 270
Exercises 274
Chapter Outline 275
Pronunciation Key 275
Chapter Exercises 276
exercises.com 280
Dataset Exercises 280
Chapter
9 Estimation and Confidence
Intervals 282
Introduction 283
Point Estimates and Confidence Intervals 283
Known _ or a Large Sample 283
A Computer Simulation 288
Exercises 290
Unknown Population Standard Deviation and
a Small Sample 291
Exercises 296
A Confidence Interval for a Proportion 297
Exercises 299
Finite-Population Correction Factor 300
Exercises 301
Choosing an Appropriate Sample Size 301
Exercises 304
Chapter Outline 305
Pronunciation Key 306
Chapter Exercises 306
exercises.com 309
Dataset Exercises 309
Software Commands 310
A Review of Chapters 8 and 9 312
Glossary 312
Exercises 313
Case 315
Chapter
10 One-Sample Tests of
Hypothesis 316
Introduction 317
What Is a Hypothesis? 317
What Is Hypothesis Testing? 318
Five-Step Procedure for
Testing a Hypothesis 318
Step 1: State the Null Hypothesis (H0) and
the Alternate Hypothesis (H1) 319
Step 2: Select a Level of Significance 320
Step 3: Select the Test Statistic 321
Step 4: Formulate the Decision Rule 321
Step 5: Make a Decision 322
One-Tailed and Two-Tailed Tests of
Significance 323
Testing for a Population Mean with a Known
Population Standard Deviation 324
A Two-Tailed Test 324
A One-Tailed Test 327
p-Value in Hypothesis Testing 328
Testing for a Population Mean: Large Sample,
Population Standard Deviation Unknown 329
Exercises 331
Tests Concerning Proportions 331
Exercises 334
Testing for a Population Mean: Small Sample,
Population Standard Deviation Unknown 335
Exercises 340
A Software Solution 341
Exercises 343
Type II Error 344
Exercises 347
Chapter Outline 347
Pronunciation Key 348
Chapter Exercises 348
exercises.com 352
Dataset Exercises 352
Software Commands 353
Chapter
11 Two-Sample Tests of
Hypothesis 355
Introduction 356
Two-Sample Tests of Hypothesis: Independent
Samples 356
Exercises 361
Exercises 364
Comparing Population Means with Small
Samples 366
Exercises 369
Two-Sample Tests of Hypothesis: Dependent
Samples 370
Comparing Dependent and
Independent Samples 374
Exercises 376
Chapter Outline 377
Pronunciation Key 378
Chapter Exercises 378
exercises.com 383
Dataset Exercises 383
Software Commands 384
Chapter
12 Analysis of Variance 386
Introduction 387
The F Distribution 387
Comparing Two Population Variances 388
Exercises 391
ANOVA Assumptions 392
The ANOVA Test 394
Exercises 401
Means 402
Exercises 404
Two-Way Analysis of Variance 406
Exercises 410
Chapter Outline 411
Pronunciation Key 412
Chapter Exercises 413
exercises.com 419
Dataset Exercises 419
Software Commands 420
A Review of Chapters 10?12 423
Glossary 423
Exercises 424
Cases 427
Chapter
13 Linear Regression and
Correlation 428
Introduction 429
What Is Correlation Analysis? 429
The Coefficient of Correlation 431
The Coefficient of Determination 435
Correlation and Cause 436
Exercises 436
Testing the Significance of the Correlation
Coefficient 438
Exercises 440
Regression Analysis 440
Least Squares Principle 441
Drawing the Line of Regression 443
Exercises 444
The Standard Error of Estimate 446
Assumptions Underlying Linear
Regression 449
Exercises 450
Confidence Intervals and Prediction
Intervals 451
Exercises 454
More on the Coefficient of Determination 454
Exercises 457
The Relationships among the Coefficient of
Correlation, the Coefficient of Determination, and
the Standard Error of Estimate 457
Transforming Data 459
Exercises 461
Chapter Outline 462
Pronunciation Key 463
Chapter Exercises 463
exercises.com 470
Dataset Exercises 471
Software Commands 472
Chapter
14 Multiple Regression and
Correlation Analysis 474
Introduction 475
Multiple Regression Analysis 475
Inferences in Multiple Linear Regression 476
Exercises 479
Multiple Standard Error of Estimate 481
Correlation 482
The ANOVA Table 483
Exercises 485
Evaluating the Regression Equation 485
Using a Scatter Diagram 485
Correlation Matrix 486
Global Test: Testing the Multiple Regression
Model 487
Evaluating Individual
Regression Coefficients 489
Qualitative Independent Variables 492
Exercises 494
Analysis of Residuals 495
Chapter Outline 500
Pronunciation Key 501
Chapter Exercises 501
exercises.com 513
Dataset Exercises 514
Software Commands 515
A Review of Chapters 13 and 14 518
Glossary 518
Exercises 519
Cases 521
Chapter
15 Nonparametric Methods:
Chi-Square Applications 522
Introduction 523
Goodness-of-Fit Test: Equal Expected
Frequencies 523
Exercises 528
Goodness-of-Fit Test: Unequal Expected
Frequencies 529
Limitations of Chi-Square 531
Exercises 533
Contingency Table Analysis 534
Exercises 538
Chapter Outline 539
Pronunciation Key 539
Chapter Exercises 539
exercises.com 542
Dataset Exercises 543
Software Commands 544
Chapter
16 Nonparametric Methods: Analysis
of Ranked Data 546
Introduction 547
The Sign Test 547
Exercises 551
Using the Normal Approximation to the
Binomial 552
Exercises 554
Testing a Hypothesis about a Median 554
Exercises 555
Wilcoxon Signed-Rank Test 556
Exercises 559
Wilcoxon Rank-Sum Test 561
Exercises 564
Kruskal-Wallis Test: Analysis of Variance by
Ranks 564
Exercises 568
Rank-Order Correlation 569
Testing the Significance of rs 571
Exercises 572
Chapter Outline 573
Pronunciation Key 575
Chapter Exercises 575
exercises.com 577
Dataset Exercises 578
Software Commands 579
A Review of Chapters 15 and 16 582
Glossary 582
Exercises 582
Cases 584
Chapter
17 Statistical Quality
Control 586
Introduction 587
A Brief History of Quality Control 587
Causes of Variation 590
Diagnostic Charts 590
Pareto Charts 591
Fishbone Diagram 592
Exercises 594
Purpose and Types of Quality
Control Charts 594
Control Charts for Variables 595
Range Chart 598
Some In-Control and Out-of-Control
Situations 599
Exercises 601
Attribute Control Charts 602
Percent Defective Chart 602
c-Bar Chart 604
Exercises 605
Acceptance Sampling 606
Exercises 609
Chapter Outline 610
Pronunciation Key 610
Chapter Exercises 611
Software Commands 615
Chapter
18 Index Numbers 618
Introduction 619
Simple Index Numbers 619
Why Convert Data to Indexes? 622
Construction of Index Numbers 622
Exercises 624
Unweighted Indexes 624
Simple Average of the Price Indexes 624
Simple Aggregate Index 625
Weighted Indexes 626
Laspeyres? Price Index 626
Paasche?s Price Index 627
Fisher?s Ideal Index 629
Exercises 630
Value Index 631
Exercises 632
Special-Purpose Indexes 632
Exercises 636
Consumer Price Index 637
Special Uses of the
Consumer Price Index 638
Shifting the Base 640
Exercises 642
Chapter Outline 643
Chapter Exercises 644
exercises.com 647
Software Commands 648
Chapter
19 Time Series and
Forecasting 650
Introduction 651
Components of a Time Series 651
Secular Trend 651
Cyclical Variation 653
Seasonal Variation 654
Irregular Variation 654
The Moving-Average Method 655
Weighted Moving Average 658
Exercises 660
Linear Trend 661
Least Squares Method 662
Exercises 664
Nonlinear Trends 665
Exercises 667
Seasonal Variation 668
Determining a Seasonal Index 668
Exercises 673
Deseasonalizing Data 674
Using Deseasonalized Data to Forecast 675
Exercises 677
Chapter Outline 678
Chapter Exercises 678
exercises.com 684
Dataset Exercises 684
Software Commands 685
Chapter
20 An Introduction to Decision
Theory 687
Introduction 688
Elements of a Decision 688
A Case Involving Decision Making under
Conditions of Uncertainty 689
Payoff Table 689
Expected Payoff 690
Exercises 691
Opportunity Loss 692
Exercises 693
Expected Opportunity Loss 693
Exercises 694
Maximin, Maximax, and Minimax Regret
Strategies 694
Value of Perfect Information 694
Sensitivity Analysis 696
Exercises 697
Decision Trees 697
Chapter Outline 699
Chapter Exercises 700
Appendixes
Covariance 706
Appendix A
Binomial Probability Distribution 713
Appendix B
Critical Values of Chi-Square 718
Appendix C
Poisson Distribution 719
Appendix D
Areas under the Normal Curve 720
Appendix E
Table of Random Numbers 721
Appendix F
Student?s t Distribution 722
Appendix G
Critical Values of the F Distribution 723
Appendix H
Wilcoxon T Values 725
Appendix I
Factors for Control Charts 726
Appendix J
Dataset 1?Real Estate 727
Appendix K
Dataset 2?Major League Baseball 730
Appendix L
Dataset 3?Wages and Wage Earners 732
Appendix M
Dataset 4?CIA International Economic and
Demographic Data 736
Appendix N
Banking Dataset?Case 739
Appendix O
Whitner Autoplex 740
Appendix P
Getting Started with MegaStat 741
Appendix Q
Visual Statistics 745
Answers to Odd-Numbered Chapter Exercises 751
Answers to Odd-Numbered Review Exercises 789
Photo Credits 793
Index 795
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Library of Congress Subject Headings for this publication:

Social sciences -- Statistical methods.
Economics -- Statistical methods.
Commercial statistics.