Statistical Techniques in Business & Economics, Eighteenth Edition
By Douglas A. Lind, William G. Marchal and Samuel A. Wathen
Contents:
A Note from the Authors vi
1 What Is Statistics? 1
Introduction 2
Why Study Statistics? 2
What Is Meant by Statistics? 3
Types of Statistics 4
Descriptive Statistics 4
Inferential Statistics 5
Types of Variables 6
Levels of Measurement 7
Nominal-Level Data 7
Ordinal-Level Data 8
Interval-Level Data 9
Ratio-Level Data 10
EXERCISES 11
Ethics and Statistics 12
Basic Business Analytics 12
Chapter Summary 14
Chapter Exercises 14
Data Analytics 17
2 Describing Data:
Frequency Tables, Frequency Distributions, and Graphic Presentation 18
Introduction 19
Constructing Frequency Tables 19
Relative Class Frequencies 20
Graphic Presentation of Qualitative Data 21
EXERCISES 25
Constructing Frequency Distributions 26
Relative Frequency Distribution 30
EXERCISES 31
Graphic Presentation of a Distribution 32
Histogram 32
Frequency Polygon 35
EXERCISES 37
Cumulative Distributions 38
EXERCISES 41
Chapter Summary 42
Chapter Exercises 43
Data Analytics 50
3 Describing Data:
Numerical Measures 51
Introduction 52
Measures of Location 52
The Population Mean 53
The Sample Mean 54
Properties of the Arithmetic Mean 55
EXERCISES 56
The Median 57
The Mode 59
Software Solution 61
EXERCISES 61
The Relative Positions of the Mean, Median, and Mode 63
EXERCISES 65
The Weighted Mean 65
EXERCISES 67
The Geometric Mean 67
EXERCISES 69
Why Study Dispersion? 69
Range 70
Variance 71
EXERCISES 73
Population Variance 74
Population Standard Deviation 76
EXERCISES 76
Sample Variance and Standard Deviation 77
Software Solution 78
EXERCISES 79
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 82
Arithmetic Mean of Grouped Data 82
Standard Deviation of Grouped Data 83
EXERCISES 85
Ethics and Reporting Results 86
Chapter Summary 86
Chapter Exercises 88
Data Analytics 92
4 Describing Data:
Displaying and Exploring Data 94
Introduction 95
Dot Plots 95
EXERCISES 97
Measures of Position 98
Quartiles, Deciles, and Percentiles 98
EXERCISES 102
Box Plots 102
EXERCISES 105
Skewness 106
EXERCISES 109
Describing the Relationship between
Two Variables 110
Correlation Coefficient 111
Contingency Tables 113
EXERCISES 115
Chapter Summary 116
Pronunciation Key 117
Chapter Exercises 117
Data Analytics 123
A REVIEW OF CHAPTERS 1–4 123
PROBLEMS 124
CASES 126
PRACTICE TEST 127
5 A Survey of Probability Concepts 130
Introduction 131
What Is a Probability? 132
Approaches to Assigning Probabilities 134
Classical Probability 134
Empirical Probability 135
Subjective Probability 137
EXERCISES 138
Rules of Addition for Computing Probabilities 139
Special Rule of Addition 139
Complement Rule 141
The General Rule of Addition 142
EXERCISES 144
Rules of Multiplication to Calculate Probability 145
Special Rule of Multiplication 145
General Rule of Multiplication 146
Contingency Tables 148
Tree Diagrams 151
EXERCISES 153
Bayes’ Theorem 155
EXERCISES 159
Principles of Counting 159
The Multiplication Formula 159
The Permutation Formula 161
The Combination Formula 163
EXERCISES 165
Chapter Summary 165
Pronunciation Key 166
Chapter Exercises 166
Data Analytics 172
6 Discrete Probability
Distributions 173
Introduction 174
What Is a Probability Distribution? 174
Random Variables 176
Discrete Random Variable 177
Continuous Random Variable 178
The Mean, Variance, and Standard Deviation of a Discrete Probability Distribution 178
Mean 178
Variance and Standard Deviation 179
EXERCISES 181
Binomial Probability Distribution 182
How Is a Binomial Probability Computed? 184
Binomial Probability Tables 186
EXERCISES 189
Cumulative Binomial Probability Distributions 190
EXERCISES 192
Hypergeometric Probability Distribution 192
EXERCISES 196
Poisson Probability Distribution 196
EXERCISES 201
Chapter Summary 201
Chapter Exercises 202
Data Analytics 207
7 Continuous Probability
Distributions 208
Introduction 209
The Family of Uniform Probability
Distributions 209
EXERCISES 212
The Family of Normal Probability Distributions 213
The Standard Normal Probability Distribution 216
Applications of the Standard Normal Distribution 217
The Empirical Rule 217
EXERCISES 219
Finding Areas under the Normal Curve 220
EXERCISES 223
EXERCISES 225
EXERCISES 228
The Family of Exponential Distributions 228
EXERCISES 233
Chapter Summary 234
Chapter Exercises 235
Data Analytics 238
A REVIEW OF CHAPTERS 5–7 239
PROBLEMS 239
CASES 241
PRACTICE TEST 242
8 Sampling, Sampling
Methods, and the Central Limit Theorem 244
Introduction 245
Research and Sampling 245
Sampling Methods 246
Simple Random Sampling 246
Systematic Random Sampling 249
Stratified Random Sampling 250
Cluster Sampling 251
EXERCISES 252
Sample Mean as a Random Variable 254
Sampling Distribution of the Sample Mean 255
EXERCISES 259
The Central Limit Theorem 260
Standard Error of The Mean 266
EXERCISES 266
Using the Sampling Distribution of the Sample Mean 267
EXERCISES 270
Chapter Summary 270
Pronunciation Key 271
Chapter Exercises 271
Data Analytics 276
9 Estimation and Confidence
Intervals 277
Introduction 278
Point Estimate for a Population Mean 278
Confidence Intervals for a Population Mean 279
Population Standard Deviation, Known σ 279
A Computer Simulation 284
EXERCISES 286
Population Standard Deviation, σ Unknown 287
EXERCISES 294
A Confidence Interval for a Population Proportion 295
EXERCISES 298
Choosing an Appropriate Sample Size 298
Sample Size to Estimate a Population Mean 299
Sample Size to Estimate a Population
Proportion 300
EXERCISES 302
Finite-Population Correction Factor 302
EXERCISES 304
Chapter Summary 305
Chapter Exercises 306
Data Analytics 310
A REVIEW OF CHAPTERS 8–9 310
PROBLEMS 311
CASES 312
PRACTICE TEST 312
10 One-Sample Tests of Hypothesis 314
Introduction 315
What Is Hypothesis Testing? 315
Six-Step Procedure for Testing a Hypothesis 316
Step 1: State the Null Hypothesis (H0) and the Alternate Hypothesis (H1) 316
Step 2: Select a Level of Significance 317
Step 3: Select the Test Statistic 319
Step 4: Formulate the Decision Rule 319
Step 5: Make a Decision 320
Step 6: Interpret the Result 320
One-Tailed and Two-Tailed Hypothesis Tests 321
Hypothesis Testing for a Population Mean: Known Population Standard Deviation 323
A Two-Tailed Test 323
A One-Tailed Test 326
p-Value in Hypothesis Testing 327
EXERCISES 329
Hypothesis Testing for a Population Mean: Population Standard Deviation Unknown 330
EXERCISES 333
A Statistical Software Solution 334
EXERCISES 336
Type II Error 337
EXERCISES 340
Chapter Summary 341
Pronunciation Key 342
Chapter Exercises 342
Data Analytics 346
11 Two-Sample Tests of Hypothesis 347
Introduction 348
Two-Sample Tests of Hypothesis: Independent Samples 348
EXERCISES 353
Comparing Population Means with Unknown Population Standard Deviations 354
Two-Sample Pooled Test 354
EXERCISES 358
Unequal Population Standard Deviations 360
EXERCISES 363
Two-Sample Tests of Hypothesis: Dependent Samples 364
Comparing Dependent and Independent Samples 367
EXERCISES 370
Chapter Summary 371
Pronunciation Key 372
Chapter Exercises 373
Data Analytics 381
12 Analysis of Variance 382
Introduction 383
Comparing Two Population Variances 383
The F-Distribution 383
Testing a Hypothesis of Equal Population Variances 384
EXERCISES 387
ANOVA: Analysis of Variance 388
ANOVA Assumptions 388
The ANOVA Test 390
EXERCISES 397
Inferences about Pairs of Treatment Means 398
EXERCISES 401
Two-Way Analysis of Variance 403
EXERCISES 407
Two-Way ANOVA with Interaction 408
Interaction Plots 409
Testing for Interaction 410
Hypothesis Tests for Interaction 411
EXERCISES 414
Chapter Summary 415
Pronunciation Key 416
Chapter Exercises 417
Data Analytics 427
A REVIEW OF CHAPTERS 10–12 427
PROBLEMS 428
CASES 431
PRACTICE TEST 431
13 Correlation and Linear Regression 433
Introduction 434
What Is Correlation Analysis? 434
The Correlation Coefficient 437
EXERCISES 442
Testing the Significance of the Correlation Coefficient 444
EXERCISES 447
Regression Analysis 448
Least Squares Principle 448
Drawing the Regression Line 451
EXERCISES 454
Testing the Significance of the Slope 456
EXERCISES 458
Evaluating a Regression Equation’s
Ability to Predict 459
The Standard Error of Estimate 459
The Coefficient of Determination 460
EXERCISES 461
Relationships among the Correlation
Coefficient, the Coefficient of
Determination, and the Standard
Error of Estimate 461
EXERCISES 463
Interval Estimates of Prediction 464
Assumptions Underlying Linear
Regression 464
Constructing Confidence and Prediction
Intervals 465
EXERCISES 468
Transforming Data 468
EXERCISES 471
Chapter Summary 473
Pronunciation Key 474
Chapter Exercises 475
Data Analytics 484
14 Multiple Regression
Analysis 485
Introduction 486
Multiple Regression Analysis 486
EXERCISES 490
Evaluating a Multiple Regression
Equation 492
The ANOVA Table 492
Multiple Standard Error of Estimate 493
Coefficient of Multiple Determination 494
Adjusted Coefficient of Determination 495
EXERCISES 496
Inferences in Multiple Linear Regression 496
Global Test: Testing the Multiple
Regression Model 496
Evaluating Individual Regression
Coefficients 499
EXERCISES 502
Evaluating the Assumptions
of Multiple Regression 503
Linear Relationship 504
Variation in Residuals Same for Large and Small ŷ
Values 505
Distribution of Residuals 506
Multicollinearity 506
Independent Observations 508
Qualitative Independent Variables 509
Regression Models with Interaction 512
Stepwise Regression 514
EXERCISES 516
Review of Multiple Regression 518
Chapter Summary 524
Pronunciation Key 525
Chapter Exercises 526
Data Analytics 536
A REVIEW OF CHAPTERS 13–14 537
PROBLEMS 538
CASES 539
PRACTICE TEST 540
15 Nonparametric Methods:
Nominal Level Hypothesis Tests 542
Introduction 543
Test a Hypothesis of a Population
Proportion 543
EXERCISES 546
Two-Sample Tests about Proportions 547
EXERCISES 551
Goodness-of-Fit Tests: Comparing
Observed and Expected Frequency
Distributions 552
Hypothesis Test of Equal Expected
Frequencies 552
EXERCISES 557
Hypothesis Test of Unequal Expected
Frequencies 559
Limitations of Chi-Square 560
EXERCISES 562
Testing the Hypothesis That a
Distribution Is Normal 563
EXERCISES 566
Contingency Table Analysis 567
EXERCISES 570
Chapter Summary 571
Pronunciation Key 572
Chapter Exercises 573
Data Analytics 578
16 Nonparametric Methods:
Analysis of Ordinal Data 579
Introduction 580
The Sign Test 580
EXERCISES 584
Testing a Hypothesis About a Median 585
EXERCISES 587
Wilcoxon Signed-Rank Test for Dependent Populations 587
EXERCISES 591
Wilcoxon Rank-Sum Test for Independent Populations 592
EXERCISES 596
Kruskal-Wallis Test: Analysis of Variance by Ranks 596
EXERCISES 600
Rank-Order Correlation 602
Testing the Significance of rs 605
EXERCISES 605
Chapter Summary 607
Pronunciation Key 608
Chapter Exercises 608
Data Analytics 611
A REVIEW OF CHAPTERS 15–16 612
PROBLEMS 613
CASES 614
PRACTICE TEST 614
17 Index Numbers 616
Introduction 617
Simple Index Numbers 617
Why Convert Data to Indexes? 620
Construction of Index Numbers 620
EXERCISES 622
Unweighted Indexes 623
Simple Average of the Price Indexes 623
Simple Aggregate Index 624
Weighted Indexes 624
Laspeyres Price Index 624
Paasche Price Index 626
Fisher’s Ideal Index 627
EXERCISES 628
Value Index 629
EXERCISES 630
Special-Purpose Indexes 631
Consumer Price Index 632
Producer Price Index 633
Dow Jones Industrial Average (DJIA) 633
EXERCISES 635
Consumer Price Index 635
Special Uses of the Consumer Price Index 636
Shifting the Base 639
EXERCISES 641
Chapter Summary 642
Chapter Exercises 643
Data Analytics 647
18 Forecasting with Time Series Analysis 648
Introduction 649
Time Series Patterns 649
Trend 649
Seasonality 651
Cycles 652
Irregular Component 652
EXERCISES 653
Modeling Stationary Time Series: Forecasts Using
Simple Moving Averages 653
Forecasting Error 655
EXERCISES 658
Modeling Stationary Time Series:
Simple Exponential Smoothing 659
EXERCISES 663
Modeling Time Series with Trend:
Regression Analysis 665
Regression Analysis 666
EXERCISES 672
The Durbin-Watson Statistic 673
EXERCISES 678
Modeling Time Series with Seasonality:
Seasonal Indexing 679
EXERCISES 687
Chapter Summary 689
Chapter Exercises 689
Data Analytics 693
A REVIEW OF CHAPTERS 17–18 695
PROBLEMS 696
PRACTICE TEST 697
19 Statistical Process Control and Quality Management 698
Introduction 699
A Brief History of Quality Control 699
Six Sigma 701
Sources of Variation 702
Diagnostic Charts 703
Pareto Charts 703
Fishbone Diagrams 705
EXERCISES 706
Purpose and Types of Quality Control Charts 706
Control Charts for Variables 707
Range Charts 710
In-Control and Out-of-Control Situations 712
EXERCISES 713
Attribute Control Charts 714
p-Charts 714
c-Bar Charts 717
EXERCISES 719
Acceptance Sampling 720
EXERCISES 723
Chapter Summary 723
Pronunciation Key 724
Chapter Exercises 725
20 An Introduction to
Decision Theory
Online Only www.mhhe.com/Lind18e
Introduction
Elements of a Decision
Decision Making Under Conditions of Uncertainty
Payoff Table
Expected Payoff
EXERCISES
Opportunity Loss
EXERCISES
Expected Opportunity Loss
EXERCISES
Maximin, Maximax, and Minimax Regret Strategies
Value of Perfect Information
Sensitivity Analysis
EXERCISES
Decision Trees
Chapter Summary
Chapter Exercises
APPENDIXES 729
Appendix A: Data Sets 730
Appendix B: Tables 740
Appendix C: Answers to Odd-Numbered
Chapter Exercises 758
Review Exercises 813
Solutions to Practice Tests 815
Appendix D: Answers to Self-Review 818
Glossary 832
Index 836