Basic Business Statistics Concepts and Applications, Fourteenth Edition
By Mark L. Berenson, David M. Levine, Kathryn A. Szabat and David F. Stephan
Contents:
Preface xxiv
First Things First 1
USING STATISTICS: “The Price of Admission” 1
FTF.1 Think Differently About Statistics 2
Statistics: A Way of Thinking 2
Statistics: An Important Part of Your Business Education 3
FTF.2 Business Analytics: The Changing Face of Statistics 4
“Big Data” 4
FTF.3 Starting Point for Learning Statistics 5
Statistic 5
Can Statistics (pl., statistic) Lie? 6
FTF.4 Starting Point for Using Software 6
Using Software Properly 8
REFERENCES 9
KEY TERMS 9
EXCEL GUIDE 10
EG.1 Getting Started with Excel 10
EG.2 Entering Data 10
EG.3 Open or Save a Workbook 10
EG.4 Working with a Workbook 11
EG.5 Print a Worksheet 11
EG.6 Reviewing Worksheets 11
EG.7 If You Use the Workbook Instructions 11
JMP GUIDE 12
JG.1 Getting Started with JMP 12
JG.2 Entering Data 13
JG.3 Create New Project or Data Table 13
JG.4 Open or Save Files 13
JG.5 Print Data Tables or Report Windows 13
JG.6 JMP Script Files 13
MINITAB GUIDE 14
MG.1 Getting Started with Minitab 14
MG.2 Entering Data 14
MG.3 Open or Save Files 14
MG.4 Insert or Copy Worksheets 15
MG.5 Print Worksheets 15
1 Defining and Collecting Data 16
USING STATISTICS: Defining Moments 16
1.1 Defining Variables 17
Classifying Variables by Type 17
Measurement Scales 18
1.2 Collecting Data 19
Populations and Samples 20
Data Sources 20
1.3 Types of Sampling Methods 21
Simple Random Sample 22
Systematic Sample 22
Stratified Sample 23
Cluster Sample 23
1.4 Data Cleaning 24
Invalid Variable Values 25
Coding Errors 25
Data Integration Errors 25
Missing Values 26
Algorithmic Cleaning of Extreme Numerical Values 26
1.5 Other Data Preprocessing Tasks 26
Data Formatting 26
Stacking and Unstacking Data 27
Recoding Variables 27
1.6 Types of Survey Errors 28
Coverage Error 28
Nonresponse Error 28
Sampling Error 28
Measurement Error 29
Ethical Issues About Surveys 29
CONSIDER THIS: New Media Surveys/Old Survey Errors 29
USING STATISTICS: Defining Moments, Revisited 31
SUMMARY 31
REFERENCES 31
KEY TERMS 31
CHECKING YOUR UNDERSTANDING 32
CHAPTER REVIEW PROBLEMS 32
CASES FOR CHAPTER 1 33
Managing Ashland MultiComm Services 33
CardioGood Fitness 33
Clear Mountain State Student Survey 34
Learning with the Digital Cases 34
CHAPTER 1 EXCEL GUIDE 35
EG1.1 Defining Variables 35
EG1.2 Collecting Data 35
EG1.3 Types of Sampling Methods 35
EG1.4 Data Cleaning 36
EG1.5 Other Data Preprocessing 36
CHAPTER 1 JMP GUIDE 37
JG1.1 Defining Variables 37
JG1.2 Collecting Data 37
JG1.3 Types of Sampling Methods 37
JG1.4 Data Cleaning 38
JG1.5 Other Preprocessing Tasks 39
CHAPTER 1 MINITAB GUIDE 39
MG1.1 Defining Variables 39
MG1.2 Collecting Data 39
MG1.3 Types of Sampling Methods 39
MG1.4 Data Cleaning 40
MG1.5 Other Preprocessing Tasks 40
2 Organizing and Visualizing Variables 41
USING STATISTICS: “The Choice Is Yours” 41
2.1 Organizing Categorical Variables 42
The Summary Table 42
The Contingency Table 43
2.2 Organizing Numerical Variables 46
The Frequency Distribution 47
Classes and Excel Bins 49
The Relative Frequency Distribution and the Percentage Distribution 49
The Cumulative Distribution 51
2.3 Visualizing Categorical Variables 54
The Bar Chart 54
The Pie Chart and the Doughnut Chart 55
The Pareto Chart 56
Visualizing Two Categorical Variables 58
2.4 Visualizing Numerical Variables 61
The Stem-and-Leaf Display 61
The Histogram 61
The Percentage Polygon 63
The Cumulative Percentage Polygon (Ogive) 64
2.5 Visualizing Two Numerical Variables 67
The Scatter Plot 67
The Time-Series Plot 68
2.6 Organizing a Mix of Variables 70
Drill-down 71
2.7 Visualizing a Mix of Variables 72
Colored Scatter Plot 72
Bubble Charts 73
PivotChart (Excel) 73
Treemap (Excel, JMP) 73
Sparklines (Excel) 74
2.8 Filtering and Querying Data 75
Excel Slicers 75
2.9 Pitfalls in Organizing and Visualizing Variables 77
Obscuring Data 77
Creating False Impressions 78
Chartjunk 79
EXHIBIT: Best Practices for Creating Visual Summaries 80
USING STATISTICS: “The Choice Is Yours,” Revisited 81
SUMMARY 81
REFERENCES 82
KEY EQUATIONS 82
KEY TERMS 83
CHECKING YOUR UNDERSTANDING 83
CHAPTER REVIEW PROBLEMS 83
CASES FOR CHAPTER 2 88
Managing Ashland MultiComm Services 88
Digital Case 88
CardioGood Fitness 89
The Choice Is Yours Follow-Up 89
Clear Mountain State Student Survey 89
CHAPTER 2 EXCEL GUIDE 90
EG2.1 Organizing Categorical Variables 90
EG2.2 Organizing Numerical Variables 92
Charts Group Reference 94
EG2.3 Visualizing Categorical Variables 94
EG2.4 Visualizing Numerical Variables 96
EG2.5 Visualizing Two Numerical Variables 99
EG2.6 Organizing a Mix of Variables 100
EG2.7 Visualizing a Mix of Variables 101
EG2.8 Filtering and Querying Data 102
CHAPTER 2 JMP GUIDE 102
JG2 JMP Choices for Creating Summaries 102
JG2.1 Organizing Categorical Variables 103
JG2.2 Organizing Numerical Variables 104
JG2.3 Visualizing Categorical Variables 106
JG2.4 Visualizing Numerical Variables 107
JG2.5 Visualizing Two Numerical Variables 109
JG2.6 Organizing a Mix of Variables 110
JG2.7 Visualizing a Mix of Variables 110
JG2.8 Filtering and Querying Data 111
JMP Guide Gallery 112
CHAPTER 2 MINITAB GUIDE 113
MG2.1 Organizing Categorical Variables 113
MG2.2 Organizing Numerical Variables 113
MG2.3 Visualizing Categorical Variables 113
MG2.4 Visualizing Numerical Variables 115
MG2.5 Visualizing Two Numerical Variables 117
MG2.6 Organizing a Mix of Variables 118
MG2.7 Visualizing a Mix of Variables 118
MG2.8 Filtering and Querying Data 119
3 Numerical Descriptive Measures 120
USING STATISTICS: More Descriptive Choices 120
3.1 Measures of Central Tendency 121
The Mean 121
The Median 123
The Mode 124
The Geometric Mean 125
3.2 Measures of Variation and Shape 126
The Range 126
The Variance and the Standard Deviation 127
The Coefficient of Variation 130
Z Scores 130
Shape: Skewness 132
Shape: Kurtosis 132
3.3 Exploring Numerical Variables 137
Quartiles 137
EXHIBIT: Rules for Calculating the Quartiles from a Set
of Ranked Values 137
The Interquartile Range 139
The Five-Number Summary 139
The Boxplot 141
3.4 Numerical Descriptive Measures for a Population 143
The Population Mean 144
The Population Variance and Standard Deviation 144
The Empirical Rule 145
Chebyshev’s Theorem 146
3.5 The Covariance and the Coefficient of Correlation 148
The Covariance 148
The Coefficient of Correlation 148
3.6 Descriptive Statistics: Pitfalls and Ethical Issues 152
USING STATISTICS: More Descriptive Choices, Revisited 153
SUMMARY 153
REFERENCES 154
KEY EQUATIONS 154
KEY TERMS 154
CHECKING YOUR UNDERSTANDING 155
CHAPTER REVIEW PROBLEMS 155
CASES FOR CHAPTER 3 158
Managing Ashland MultiComm Services 158
Digital Case 158
CardioGood Fitness 158
More Descriptive Choices Follow-up 159
Clear Mountain State Student Survey 159
CHAPTER 3 EXCEL GUIDE 160
EG3.1 Measures of Central Tendency 160
EG3.2 Measures of Variation and Shape 161
EG3.3 Exploring Numerical Variables 161
EG3.4 Numerical Descriptive Measures for a Population 162
EG3.5 The Covariance and the Coefficient of Correlation 162
CHAPTER 3 JMP GUIDE 163
JG3.1 Measures of Central Tendency 163
JG3.2 Measures of Variation and Shape 163
JG3.3 Exploring Numerical Variables 164
JG3.4 Numerical Descriptive Measures for a Population 164
JG3.5 The Covariance and the Coefficient of Correlation 164
CHAPTER 3 MINITAB GUIDE 165
MG3.1 Measures of Central Tendency 165
MG3.2 Measures of Variation and Shape 166
MG3.3 Exploring Numerical Variables 166
MG3.4 Numerical Descriptive Measures for a Population 167
MG3.5 The Covariance and the Coefficient of Correlation 167
4 Basic Probability 168
USING STATISTICS: Possibilities at M&R Electronics World 168
4.1 Basic Probability Concepts 169
Events and Sample Spaces 169
Types of Probability 170
Summarizing Sample Spaces 171
Simple Probability 172
Joint Probability 173
Marginal Probability 174
General Addition Rule 174
4.2 Conditional Probability 178
Computing Conditional Probabilities 178
Decision Trees 179
Independence 181
Multiplication Rules 182
Marginal Probability Using the General Multiplication Rule 183
4.3 Ethical Issues and Probability 185
4.4 Bayes’ Theorem 186
CONSIDER THIS: Divine Providence and Spam 188
4.5 Counting Rules 189
USING STATISTICS: Possibilities at M&R Electronics World, Revisited 192
SUMMARY 193
REFERENCES 193
KEY EQUATIONS 193
KEY TERMS 194
CHECKING YOUR UNDERSTANDING 194
CHAPTER REVIEW PROBLEMS 194
CASES FOR CHAPTER 4 196
Digital Case 196
CardioGood Fitness 196
The Choice Is Yours Follow-Up 196
Clear Mountain State Student Survey 196
CHAPTER 4 EXCEL GUIDE 197
EG4.1 Basic Probability Concepts 197
EG4.4 Bayes’ Theorem 197
EG4.5 Counting Rules 197
CHAPTER 4 JMP
JG4.4 Bayes’ Theorem 198
CHAPTER 4 MINITAB GUIDE 198
MG4.5 Counting Rules 198
5 Discrete Probability
Distributions 199
USING STATISTICS: Events of Interest at Ricknel Home Centers 199
5.1 The Probability Distribution for a Discrete Variable 200
Expected Value of a Discrete Variable 200
Variance and Standard Deviation of a Discrete Variable 201
5.2 Binomial Distribution 204
EXHIBIT: Properties of the Binomial Distribution 204
Histograms for Discrete Variables 207
Summary Measures for the Binomial Distribution 208
5.3 Poisson Distribution 211
5.4 Covariance of a Probability Distribution and Its Application in Finance 214
5.5 Hypergeometric Distribution (online) 214
5.6 Using the Poisson Distribution to Approximate the Binomial Distribution (online) 214
USING STATISTICS: Events of Interest …. , Revisited 215
SUMMARY 215
REFERENCES 215
KEY EQUATIONS 215
KEY TERMS 216
CHECKING YOUR UNDERSTANDING 216
CHAPTER REVIEW PROBLEMS 216
CASES FOR CHAPTER 5 218
Managing Ashland MultiComm Services 218
Digital Case 218
CHAPTER 5 EXCEL GUIDE 219
EG5.1 The Probability Distribution for a Discrete Variable 219
EG5.2 Binomial Distribution 219
EG5.3 Poisson Distribution 219
CHAPTER 5 JMP GUIDE 220
JG5.1 The Probability Distribution for a Discrete Variable 220
JG5.2 Binomial Distribution 220
JG5.3 Poisson Distribution 221
CHAPTER 5 MINITAB GUIDE 221
MG5.1 The Probability Distribution for a Discrete Variable 221
MG5.2 Binomial Distribution 222
MG5.3 Poisson Distribution 222
6 The Normal Distribution
and Other Continuous
Distributions 223
USING STATISTICS: Normal Load Times at MyTVLab 223
6.1 Continuous Probability Distributions 224
6.2 The Normal Distribution 224
EXHIBIT: Normal Distribution Important Theoretical Properties 225
Role of the Mean and the Standard Deviation 226
Calculating Normal Probabilities 227
VISUAL EXPLORATIONS: Exploring the Normal Distribution 231
Finding X Values 232
CONSIDER THIS: What Is Normal? 235
6.3 Evaluating Normality 237
Comparing Data Characteristics to Theoretical Properties 237
Constructing the Normal Probability Plot 238
6.4 The Uniform Distribution 241
6.5 The Exponential Distribution (online) 243
6.6 The Normal Approximation to the Binomial Distribution (online) 243
USING STATISTICS: Normal Load Times … , Revisited 243
SUMMARY 243
REFERENCES 244
KEY EQUATIONS 244
KEY TERMS 244
CHECKING YOUR UNDERSTANDING 245
CHAPTER REVIEW PROBLEMS 245
CASES FOR CHAPTER 6 246
Managing Ashland MultiComm Services 246
CardioGood Fitness 247
More Descriptive Choices Follow-up 247
Clear Mountain State Student Survey 247
Digital Case 247
CHAPTER 6 EXCEL GUIDE 248
EG6.2 The Normal Distribution 248
EG6.3 Evaluating Normality 248
CHAPTER 6 JMP GUIDE 249
JG6.2 The Normal Distribution 249
JG6.3 Evaluating Normality 249
CHAPTER 6 MINITAB GUIDE 250
MG6.2 The Normal Distribution 250
MG6.3 Evaluating Normality 250
7 Sampling Distributions 252
USING STATISTICS: Sampling Oxford Cereals 252
7.1 Sampling Distributions 253
7.2 Sampling Distribution of the Mean 253
The Unbiased Property of the Sample Mean 253
Standard Error of the Mean 255
Sampling from Normally Distributed Populations 256
Sampling from Non-normally Distributed Populations—The Central Limit Theorem 259
EXHIBIT: Normality and the Sampling Distribution of the Mean 260
VISUAL EXPLORATIONS: Exploring Sampling Distributions 263
7.3 Sampling Distribution of the Proportion 264
7.4 Sampling from Finite Populations (online) 267
USING STATISTICS: Sampling Oxford Cereals, Revisited 267
SUMMARY 268
REFERENCES 268
KEY EQUATIONS 268
KEY TERMS 268
CHECKING YOUR UNDERSTANDING 269
CHAPTER REVIEW PROBLEMS 269
CASES FOR CHAPTER 7 270
Managing Ashland MultiComm Services 270
Digital Case 271
CHAPTER 7 EXCEL GUIDE 272
EG7.2 Sampling Distribution of the Mean 272
CHAPTER 7 JMP GUIDE 273
JG7.2 Sampling Distribution of the Mean 273
CHAPTER 7 MINITAB GUIDE 274
MG7.2 Sampling Distribution of the Mean 274
8 Confidence Interval Estimation 275
USING STATISTICS: Getting Estimates at Ricknel Home Centers 275
8.1 Confidence Interval Estimate for the Mean (s Known) 276
Sampling Error 277
Can You Ever Know the Population Standard Deviation? 280
8.2 Confidence Interval Estimate for the Mean (s Unknown) 281
Student’s t Distribution 282
The Concept of Degrees of Freedom 282
Properties of the t Distribution 282
The Confidence Interval Statement 284
8.3 Confidence Interval Estimate for the Proportion 289
8.4 Determining Sample Size 292
Sample Size Determination for the Mean 292
Sample Size Determination for the Proportion 294
8.5 Confidence Interval Estimation and Ethical Issues 297
8.6 Application of Confidence Interval Estimation in Auditing (online) 297
8.7 Estimation and Sample Size Estimation for Finite Populations (online) 298
8.8 Bootstrapping (online) 298
USING STATISTICS: Getting Estimates …. , Revisited 298
SUMMARY 298
REFERENCES 299
KEY EQUATIONS 299
KEY TERMS 299
CHECKING YOUR UNDERSTANDING 299
CHAPTER REVIEW PROBLEMS 300
CASES FOR CHAPTER 8 302
Managing Ashland MultiComm Services 302
Digital Case 303
Sure Value Convenience Stores 304
CardioGood Fitness 304
More Descriptive Choices Follow-Up 304
Clear Mountain State Student Survey 304
CHAPTER 8 EXCEL GUIDE 305
EG8.1 Confidence Interval Estimate for the Mean (s Known) 305
EG8.2 Confidence Interval Estimate for the Mean (s Unknown) 305
EG8.3 Confidence Interval Estimate for the Proportion 306
EG8.4 Determining Sample Size 306
CHAPTER 8 JMP GUIDE 307
JG8.1 Confidence Interval Estimate for the Mean (s Known) 307
JG8.2 Confidence Interval Estimate for the Mean (s Unknown) 307
JG8.3 Confidence Interval Estimate for the Proportion 308
JG8.4 Determining Sample Size 308
CHAPTER 8 MINITAB GUIDE 309
MG8.1 Confidence Interval Estimate for the Mean (s Known) 309
MG8.2 Confidence Interval Estimate for the Mean (s Unknown) 309
MG8.3 Confidence Interval Estimate for the Proportion 310
MG8.4 Determining Sample Size 310
9 Fundamentals of Hypothesis
Testing: One-Sample Tests 311
USING STATISTICS: Significant Testing at Oxford Cereals 311
9.1 Fundamentals of Hypothesis Testing 312
EXHIBIT: Fundamental Hypothesis Testing Concepts 313
The Critical Value of the Test Statistic 313
Regions of Rejection and Nonrejection 314
Risks in Decision Making Using Hypothesis Testing 314
Z Test for the Mean (s Known) 316
Hypothesis Testing Using the Critical Value Approach 317
EXHIBIT: The Critical Value Approach to Hypothesis Testing 318
Hypothesis Testing Using the p-Value Approach 320
EXHIBIT: The p-Value Approach to Hypothesis Testing 321
A Connection Between Confidence Interval Estimation and Hypothesis Testing 322
Can You Ever Know the Population Standard Deviation? 323
9.2 t Test of Hypothesis for the Mean (s Unknown) 324
The Critical Value Approach 325
p-Value Approach 326
Checking the Normality Assumption 327
9.3 One-Tail Tests 330
The Critical Value Approach 330
The p-Value Approach 331
EXHIBIT: The Null and Alternative Hypotheses in One-Tail Tests 333
9.4 Z Test of Hypothesis for the Proportion 334
The Critical Value Approach 335
The p-Value Approach 336
9.5 Potential Hypothesis-Testing Pitfalls and Ethical Issues 338
EXHIBIT: Questions for the Planning Stage of Hypothesis
Testing 338
Statistical Significance Versus Practical Significance 338
Statistical Insignificance Versus Importance 339
Reporting of Findings 339
Ethical Issues 339
9.6 Power of the Test (online) 339
USING STATISTICS: Significant Testing …. Revisited 340
SUMMARY 340
REFERENCES 340
KEY EQUATIONS 341
KEY TERMS 341
CHECKING YOUR UNDERSTANDING 341
CHAPTER REVIEW PROBLEMS 341
CASES FOR CHAPTER 9 343
Managing Ashland MultiComm Services 343
Digital Case 343
Sure Value Convenience Stores 344
CHPATER 9 EXCEL GUIDE 345
EG9.1 Fundamentals of Hypothesis Testing 345
EG9.2 t Test Of Hypothesis for The Mean (s Unknown) 345
EG9.3 One-Tail Tests 346
EG9.4 Z Test Of Hypothesis For The Proportion 346
CHAPTER 9 JMP GUIDE 347
JG9.1 Fundamentals of Hypothesis Testing 347
JG9.2 t Test of Hypothesis for the Mean (s Unknown) 347
JG9.3 One-Tail Tests 348
JG9.4 Z Test Of Hypothesis For The Proportion 348
CHAPTER 9 MINITAB GUIDE 348
MG9.1 Fundamentals of Hypothesis Testing 348
MG9.2 t Test Of Hypothesis for The Mean (s Unknown) 349
MG9.3 One-Tail Tests 349
MG9.4 Z Test Of Hypothesis for The Proportion 349
10 Two-Sample Tests 351
USING STATISTICS: Differing Means for Selling
Streaming Media Players at Arlingtons? 351
10.1 Comparing the Means of Two Independent Populations 352
Pooled-Variance t Test for the Difference Between
Two Means Assuming Equal Variances 352
Evaluating the Normality Assumption 355
Confidence Interval Estimate for the Difference Between Two Means 357
Separate-Variance t Test for the Difference Between
Two Means, Assuming Unequal Variances 358
CONSIDER THIS: Do People Really Do This? 359
10.2 Comparing the Means of Two Related Populations 361
Paired t Test 362
Confidence Interval Estimate for the Mean Difference 367
10.3 Comparing the Proportions of Two Independent
Populations 369
Z Test for the Difference Between Two Proportions 369
Confidence Interval Estimate for the Difference Between
Two Proportions 374
10.4 F Test for the Ratio of Two Variances 376
10.5 Effect Size (online) 380
USING STATISTICS: Differing Means for Selling … ,
Revisited 381
SUMMARY 381
REFERENCES 382
KEY EQUATIONS 382
KEY TERMS 383
CHECKING YOUR UNDERSTANDING 383
CHAPTER REVIEW PROBLEMS 383
CASES FOR CHAPTER 10 385
Managing Ashland MultiComm Services 385
Digital Case 386
Sure Value Convenience Stores 386
CardioGood Fitness 386
More Descriptive Choices Follow-Up 386
Clear Mountain State Student Survey 387
CHAPTER 10 EXCEL GUIDE 388
EG10.1 Comparing The Means of Two Independent Populations 388
EG10.2 Comparing The Means of Two Related Populations 390
EG10.3 Comparing The Proportions of Two Independent
Populations 391
EG10.4 F Test For The Ratio of Two Variances 392
CHAPTER 10 JMP GUIDE 393
JG10.1 Comparing The Means of Two Independent Populations 393
JG10.2 Comparing The Means of Two Related Populations 394
JG10.3 Comparing The Proportions of Two Independent
Populations 394
JG10.4 F Test For The Ratio of Two Variances 394
CHAPTER 10 MINITAB GUIDE 395
MG10.1 Comparing The Means of Two Independent Populations 395
MG10.2 Comparing The Means of Two Related Populations 396
MG10.3 Comparing The Proportions of Two Independent
Populations 396
MG10.4 F Test For The Ratio of Two Variances 397
11 Analysis of Variance 398
USING STATISTICS: The Means to Find Differences at Arlingtons 398
11.1 The Completely Randomized Design: One-Way ANOVA 399
Analyzing Variation in One-Way ANOVA 400
F Test for Differences Among More Than Two Means 402
One-Way ANOVA F Test Assumptions 407
Levene Test for Homogeneity of Variance 407
Multiple Comparisons: The Tukey-Kramer Procedure 409
The Analysis of Means (ANOM) 411
11.2 The Factorial Design: Two-Way ANOVA 414
Factor and Interaction Effects 415
Testing for Factor and Interaction Effects 416
Multiple Comparisons: The Tukey Procedure 420
Visualizing Interaction Effects: The Cell Means Plot 421
Interpreting Interaction Effects 422
11.3 The Randomized Block Design (online) 426
11.4 Fixed Effects, Random Effects, and Mixed Effects Models (online) 426
USING STATISTICS: The Means to Find Differences
at Arlingtons Revisited 426
SUMMARY 426
REFERENCES 427
KEY EQUATIONS 427
KEY TERMS 428
CHECKING YOUR UNDERSTANDING 428
CHAPTER REVIEW PROBLEMS 428
CASES FOR CHAPTER 11 430
Managing Ashland MultiComm Services 430
Digital Case 431
Sure Value Convenience Stores 431
CardioGood Fitness 431
More Descriptive Choices Follow-Up 431
Clear Mountain State Student Survey 431
CHAPTER 11 EXCEL GUIDE 432
EG11.1 The Completely Randomized Design: One-Way ANOVA 432
EG11.2 The Factorial Design: Two-Way Anova 434
CHAPTER 11 JMP GUIDE 435
JG11.1 The Completely Randomized Design: One-Way ANOVA 435
JG11.2 The Factorial Design: Two-Way Anova 436
CHAPTER 11 MINITAB GUIDE 437
MG11.1 The Completely Randomized Design: One-Way ANOVA 437
MG11.2 The Factorial Design: Two-Way Anova 438
12 Chi-Square and
Nonparametric Tests 440
USING STATISTICS: Avoiding Guesswork About
Resort Guests 440
12.1 Chi-Square Test for the Difference Between Two
Proportions 441
12.2 Chi-Square Test for Differences Among More Than
Two Proportions 448
The Marascuilo Procedure 451
The Analysis of Proportions (ANOP) 453
12.3 Chi-Square Test of Independence 454
12.4 Wilcoxon Rank Sum Test for Two Independent
Populations 460
12.5 Kruskal-Wallis Rank Test for the One-Way ANOVA 466
Assumptions of the Kruskal-Wallis Rank Test 469
12.6 McNemar Test for the Difference Between Two
Proportions (Related Samples) (online) 470
12.7 Chi-Square Test for the Variance or Standard
Deviation (online) 470
12.8 Wilcoxon Signed Ranks Test for Two Related
Populations (online) 471
12.9 Friedman Rank Test for the Randomized Block
Design (online) 471
USING STATISTICS: Avoiding Guesswork … ,
Revisited 471
SUMMARY 471
REFERENCES 472
KEY EQUATIONS 472
KEY TERMS 473
CHECKING YOUR UNDERSTANDING 473
CHAPTER REVIEW PROBLEMS 473
CASES FOR CHAPTER 12 475
Managing Ashland MultiComm Services 475
Digital Case 476
Sure Value Convenience Stores 476
CardioGood Fitness 476
More Descriptive Choices Follow-Up 477
Clear Mountain State Student Survey 477
CHAPTER 12 EXCEL GUIDE 478
EG12.1 Chi-Square Test for the Difference Between
Two Proportions 478
EG12.2 Chi-Square Test for Differences Among More Than
Two Proportions 478
EG12.3 Chi-Square Test of Independence 479
EG12.4 Wilcoxon Rank Sum Test: A Nonparametric Method for
Two Independent Populations 479
EG12.5 Kruskal-Wallis Rank Test: A Nonparametric Method for
the One-Way ANOVA 480
CHAPTER 12 JMP GUIDE 481
JG12.1 Chi-Square Test for the Difference Between
Two Proportions 481
JG12.2 Chi-Square Test tor Difference Among More Than
Two Proportions 481
JG12.3 Chi-Square Test Of Independence 481
JG12.4 Wilcoxon Rank Sum Test For Two Independent
Populations 481
JG12.5 Kruskal-Wallis Rank Test For The One-Way Anova 482
CHAPTER 12 MINITAB GUIDE 482
MG12.1 Chi-Square Test for The Difference Between
Two Proportions 482
MG12.2 Chi-Square Test for Differences Among More Than
Two Proportions 483
MG12.3 Chi-Square Test of Independence 483
MG12.4 Wilcoxon Rank Sum Test: A Nonparametric Method
for Two Independent Populations 483
MG12.5 Kruskal-Wallis Rank Test: A Nonparametric Method
for The One-Way ANOVA 483
13 Simple Linear Regression 484
USING STATISTICS: Knowing Customers at Sunflowers Apparel 484
Preliminary Analysis 485
13.1 Simple Linear Regression Models 486
13.2 Determining the Simple Linear Regression Equation 487
The Least-Squares Method 487
Predictions in Regression Analysis: Interpolation Versus Extrapolation 490
Computing the Y Intercept, b0 and the Slope, b1 491
VISUAL EXPLORATIONS: Exploring Simple Linear
Regression Coefficients 493
13.3 Measures of Variation 495
Computing the Sum of Squares 495
The Coefficient of Determination 496
Standard Error of the Estimate 498
13.4 Assumptions of Regression 500
13.5 Residual Analysis 500
Evaluating the Assumptions 500
13.6 Measuring Autocorrelation: The Durbin-Watson Statistic 504
Residual Plots to Detect Autocorrelation 504
The Durbin-Watson Statistic 505
13.7 Inferences About the Slope and Correlation Coefficient 508
t Test for the Slope 508
F Test for the Slope 509
Confidence Interval Estimate for the Slope 511
13.8 Estimation of Mean Values and Prediction of
Individual Values 514
The Confidence Interval Estimate for the Mean Response 515
The Prediction Interval for an Individual Response 516
13.9 Potential Pitfalls in Regression 518
EXHIBIT: Seven Steps for Avoiding the Potential Pitfalls 518
USING STATISTICS: Knowing Customers … , Revisited 520
SUMMARY 521
REFERENCES 522
KEY EQUATIONS 522
KEY TERMS 523
CHECKING YOUR UNDERSTANDING 523
CHAPTER REVIEW PROBLEMS 524
CASES FOR CHAPTER 13 527
Managing Ashland MultiComm Services 527
Digital Case 527
Brynne Packaging 528
CHAPTER 13 EXCEL GUIDE 529
EG13.2 Determining the Simple Linear Regression Equation 529
EG13.3 Measures of Variation 530
EG13.4 Assumptions of Regression 530
EG13.5 Residual Analysis 530
EG13.6 Measuring Autocorrelation: the Durbin-Watson Statistic 531
EG13.7 Inferences about the Slope and Correlation Coefficient 531
EG13.8 Estimation of Mean Values and Prediction of Individual Values 531
CHAPTER 13 JMP GUIDE 532
JG13.2 Determining The Simple Linear Regression Equation 532
JG13.3 Measures Of Variation 532
JG13.4 Assumptions Of Regression 532
JG13.5 Residual Analysis 532
JG13.6 Measuring Autocorrelation: The Durbin-Watson Statistic 532
JG13.7 Inferences About The Slope And Correlation Coefficient 532
JG13.8 Estimation Of Mean Values And Prediction Of Individual Values 533
CHAPTER 13 MINITAB GUIDE 534
MG13.2 Determining The Simple Linear Regression Equation 534
MG13.3 Measures Of Variation 535
MG13.4 Assumptions Of Regression 535
MG13.5 Residual Analysis 535
MG13.6 Measuring Autocorrelation: The Durbin-Watson Statistic 535
MG13.7 Inferences about The Slope and Correlation Coefficient 535
MG13.8 Estimation of Mean Values and Prediction of Individual Values 535
14 Introduction to Multiple Regression 536
USING STATISTICS: The Multiple Effects of Omni Power Bars 536
14.1 Developing a Multiple Regression Model 537
Interpreting the Regression Coefficients 538
Predicting the Dependent Variable Y 540
14.2 r2, Adjusted r2, and the Overall F Test 542
Coefficient of Multiple Determination 542
Adjusted r2 543
Test for the Significance of the Overall Multiple Regression Model 543
14.3 Multiple Regression Residual Analysis 546
14.4 Inferences About the Population Regression
Coefficients 547
Tests of Hypothesis 548
Confidence Interval Estimation 549
14.5 Testing Portions of the Multiple Regression Model 551
Coefficients of Partial Determination 555
14.6 Using Dummy Variables and Interaction Terms 557
Interactions 560
14.7 Logistic Regression 569
14.8 Influence Analysis (online) 575
USING STATISTICS: The Multiple Effects … , Revisited 575
SUMMARY 575
REFERENCES 577
KEY EQUATIONS 577
KEY TERMS 578
CHECKING YOUR UNDERSTANDING 578
CHAPTER REVIEW PROBLEMS 578
CASES FOR CHAPTER 14 581
Managing Ashland MultiComm Services 581
Digital Case 581
CHAPTER 14 EXCEL GUIDE 582
EG14.1 Developing a Multiple Regression Model 582
EG14.2 r2, Adjusted r2, and the Overall F Test 583
EG14.3 Multiple Regression Residual Analysis 583
EG14.4 Inferences about the Population Regression Coefficients 584
EG14.5 Testing Portions of the Multiple Regression Model 584
EG14.6 Using Dummy Variables and Interaction Terms 584
EG14.7 Logistic Regression 585
CHAPTER 14 JMP GUIDE 585
JG14.1 Developing a Multiple Regression Model 585
JG14.2 r2, Adjusted r2, and the Overall F Test Measures of Variation 586
JG14.3 Multiple Regression Residual Analysis 586
JG14.4 Inferences About the Population 586
JG14.5 Testing Portions of the Multiple Regression Model 587
JG14.6 Using Dummy Variables and Interaction Terms 587
JG14.7 Logistic Regression 587
CHAPTER 14 MINITAB GUIDE 588
MG14.1 Developing a Multiple Regression Model 588
MG14.2 r2, Adjusted r2, and the Overall F Test 589
MG14.3 Multiple Regression Residual Analysis 589
MG14.4 Inferences About the Population Regression Coefficients 589
MG14.5 Testing Portions of the Multiple Regression Model 589
MG14.6 Using Dummy Variables and Interaction Terms
in Regression Models 589
MG14.7 Logistic Regression 590
MG14.8 Influence Analysis 591
15 Multiple Regression Model Building 592
USING STATISTICS: Valuing Parsimony at WSTA-TV 592
15.1 Quadratic Regression Model 593
Finding the Regression Coefficients and Predicting Y 594
Testing for the Significance of the Quadratic Model 596
Testing the Quadratic Effect 597
The Coefficient of Multiple Determination 599
15.2 Using Transformations in Regression Models 601
The Square-Root Transformation 601
The Log Transformation 603
15.3 Collinearity 605
15.4 Model Building 607
EXHIBIT: Sucessful Model Building 607
The Stepwise Regression Approach to Model Building 609
The Best Subsets Approach to Model Building 610
Model Validation 613
15.5 Pitfalls in Multiple Regression and Ethical Issues 615
Pitfalls in Multiple Regression 615
Ethical Issues 616
USING STATISTICS: Valuing Parsimony … , Revisited 616
SUMMARY 617
REFERENCES 618
KEY EQUATIONS 618
KEY TERMS 618
CHECKING YOUR UNDERSTANDING 618
CHAPTER REVIEW PROBLEMS 618
CASES FOR CHAPTER 15 620
The Mountain States Potato Company 620
Sure Value Convenience Stores 621
Digital Case 621
The Craybill Instrumentation Company Case 621
More Descriptive Choices Follow-Up 622
CHAPATER 15 EXCEL GUIDE 623
EG15.1 The Quadratic Regression Model 623
EG15.2 Using Transformations in Regression Models 623
EG15.3 Collinearity 624
EG15.4 Model Building 624
CHAPATER 15 JMP GUIDE 625
JG15.1 The Quadratic Regression Model 625
JG15.2 Using Transformations in Regression Models 625
JG15.3 Collinearity 625
JG15.4 Model Building 625
CHAPATER 15 MINITAB GUIDE 626
MG15.1 The Quadratic Regression Model 626
MG15.2 Using Transformations in Regression Models 627
MG15.3 Collinearity 627
MG15.4 Model Building 627
16 Time-Series Forecasting 629
USING STATISTICS: Is the ByYourDoor Service
Trending? 629
16.1 Time Series Component Factors 630
16.2 Smoothing an Annual Time Series 632
Moving Averages 633
Exponential Smoothing 635
16.3 Least-Squares Trend Fitting and Forecasting 637
The Linear Trend Model 637
The Quadratic Trend Model 639
The Exponential Trend Model 640
Model Selection Using First, Second, and Percentage
Differences 642
EXHIBIT: Model Selection Using First, Second, and Percentage
Differences 642
16.4 Autoregressive Modeling for Trend Fitting and
Forecasting 647
Selecting an Appropriate Autoregressive Model 648
Determining the Appropriateness of a
Selected Model 649
EXHIBIT: Autoregressive Modeling Steps 651
16.5 Choosing an Appropriate Forecasting Model 655
Residual Analysis 655
The Magnitude of the Residuals Through Squared
or Absolute Differences 656
The Principle of Parsimony 656
A Comparison of Four Forecasting Methods 657
16.6 Time-Series Forecasting of Seasonal Data 659
Least-Squares Forecasting with Monthly or Quarterly Data 659
16.7 Index Numbers (online) 665
CONSIDER THIS: Let the Model User Beware 665
USING STATISTICS: Is the ByYourDoor … , Revisited 665
SUMMARY 665
REFERENCES 666
KEY EQUATIONS 666
KEY TERMS 667
CHECKING YOUR UNDERSTANDING 668
CHAPTER REVIEW PROBLEMS 668
CASES FOR CHAPTER 16 669
Managing Ashland MultiComm Services 669
Digital Case 669
CHAPTER 16 EXCEL GUIDE 670
EG16.2 Smoothing an Annual Time Series 670
EG16.3 Least-Squares Trend Fitting and Forecasting 671
EG16.4 Autoregressive Modeling for Trend Fitting and Forecasting 671
EG16.5 Choosing An Appropriate Forecasting Model 672
EG16.6 Time-Series Forecasting Of Seasonal Data 672
CHAPTER 16 JMP GUIDE 673
JG16.2 Smoothing an Annual Time Series 673
JG16.3 Least-Squares Trend Fitting and Forecasting 674
JG16.4 Autoregressive Modeling for Trend Fitting and Forecasting 674
JG16.5 Choosing an Appropriate Forecasting Model 675
JG16.6 Time-Series Forecasting of Seasonal Data 675
CHAPTER 16 MINITAB GUIDE 675
MG16.2 Smoothing an Annual Time Series 675
MG16.3 Least-Squares Trend Fitting and Forecasting 676
MG16.4 Autoregressive Modeling for Trend Fitting and
Forecasting 677
MG16.5 Choosing an Appropriate Forecasting Model 677
MG16.6 Time-Series Forecasting of Seasonal Data 677
17 Business Analytics 678
USING STATISTICS: Back to Arlingtons for the Future 678
17.1 Business Analytics Categories 679
Inferential Statistics and Predictive Analytics 680
Supervised and Unsupervised Methods 680
CONSIDER THIS: What’s My Major if I Want to be a
Data Miner? 681
17.2 Descriptive Analytics 682
Dashboards 682
Data Dimensionality and Descriptive Analytics 683
17.3 Predictive Analytics for Prediction 684
17.4 Predictive Analytics for Classification 687
17.5 Predictive Analytics for Clustering 688
17.6 Predictive Analytics for Association 691
Multidimensional scaling (MDS) 692
17.7 Text Analytics 693
17.8 Prescriptive Analytics 694
USING STATISTICS: Back to Arlingtons … , Revisited 695
REFERENCES 695
KEY EQUATIONS 696
KEY TERMS 696
CHECKING YOUR UNDERSTANDING 696
CHAPTER REVIEW PROBLEMS 696
CASES FOR CHAPTER 17 698
The Mountain States Potato Company 698
The Craybill Instrumentation Company 698
CHAPTER 17 SOFTWARE GUIDE 699
Introduction 699
SG17.2 Descriptive Analytics 699
SG17.3 Predictive Analytics for Prediction 701
SG17.4 Predictive Analytics for Classification 701
SG17.5 Predictive Analytics for Clustering 702
SG17.6 Predictive Analytics for Association 702
18 Getting Ready to Analyze
Data in the Future 704
USING STATISTICS: Mounting Future Analyses 704
18.1 Analyzing Numerical Variables 705
EXHIBIT: Questions to Ask When Analyzing Numerical Variables 705
Describe the Characteristics of a Numerical Variable? 705
Reach Conclusions About the Population Mean or the Standard Deviation? 705
Determine Whether the Mean and/or Standard Deviation
Differs Depending on the Group? 706
Determine Which Factors Affect the Value of a Variable? 706
Predict the Value of a Variable Based on the Values of Other Variables? 707
Classify or Associate Items 707
Determine Whether the Values of a Variable Are Stable
Over Time? 707
18.2 Analyzing Categorical Variables 707
EXHIBIT: Questions to Ask When Analyzing Categorical Variables 707
Describe the Proportion of Items of Interest in Each Category? 707
Reach Conclusions About the Proportion of Items of Interest? 708
Determine Whether the Proportion of Items of Interest Differs
Depending on the Group? 708
Predict the Proportion of Items of Interest Based on the
Values of Other Variables? 708
Classify or Associate Items 708
Determine Whether the Proportion of Items of Interest Is
Stable Over Time? 708
USING STATISTICS: The Future to Be Visited 709
CHAPTER REVIEW PROBLEMS 709
19 Statistical Applications in Quality Management (online) 19-1
USING STATISTICS: Finding Quality at the Beachcomber 19-1
19.1 The Theory of Control Charts 19-2
19.2 Control Chart for the Proportion: The p Chart 19-4
19.3 The Red Bead Experiment: Understanding Process Variability 19-10
19.4 Control Chart for an Area of Opportunity: The c Chart 19-11
19.5 Control Charts for the Range and the Mean 19-15
The R Chart 19-15
The X Chart 19-18
19.6 Process Capability 19-21
Customer Satisfaction and Specification Limits 19-21
Capability Indices 19-23
CPL, CPU, and Cpk 19-24
19.7 Total Quality Management 19-26
19.8 Six Sigma 19-27
The DMAIC Model 19-28
Roles in a Six Sigma Organization 19-29
Lean Six Sigma 19-29
USING STATISTICS: Finding Quality at the Beachcomber, Revisited 19-30
SUMMARY 19-30
REFERENCES 19-31
KEY EQUATIONS 19-31
KEY TERMS 19-32
CHAPTER REVIEW PROBLEMS 19-32
CASES FOR CHAPTER 19 19-34
The Harnswell Sewing Machine Company Case 19-34
Managing Ashland Multicomm Services 19-37
CHAPTER 19 EXCEL GUIDE 19-38
EG19.2 Control Chart for the Proportion: The p Chart 19-38
EG19.4 Control Chart for an Area of Opportunity: The c Chart 19-39
EG19.5 Control Charts for the Range and the Mean 19-40
EG19.6 Process Capability 19-41
CHAPTER 19 JMP GUIDE 19-41
JG19.2 Control Chart for the Proportion: The p Chart 19-41
JG19.4 Control Chart for an Area of Opportunity: The c Chart 19-41
JG19.5 Control Charts for the Range and the Mean 19-42
JG19.6 Process Capability 19-42
CHAPTER 19 MINITAB GUIDE 19-42
MG19.2 Control Chart for the Proportion: The p Chart 19-42
MG19.4 Control Chart for an Area of Opportunity:
The c Chart 19-43
MG19.5 Control Charts for the Range and the Mean 19-43
MG19.6 Process Capability 19-43
20 Decision Making (online) 20-1
USING STATISTICS: Reliable Decision Making 20-1
20.1 Payoff Tables and Decision Trees 20-2
20.2 Criteria for Decision Making 20-6
Maximax Payoff 20-6
Maximin Payoff 20-7
Expected Monetary Value 20-7
Expected Opportunity Loss 20-9
Return-to-Risk Ratio 20-11
20.3 Decision Making with Sample Information 20-16
20.4 Utility 20-21
CONSIDER THIS: Risky Business 20-22
USING STATISTICS: Reliable Decision-Making,
Revisited 20-22
SUMMARY 20-23
REFERENCES 20-23
KEY EQUATIONS 20-23
KEY TERMS 20-23
CHAPTER REVIEW PROBLEMS 20-23
CASES FOR CHAPTER 20 20-26
Digital Case 20-26
CHAPTER 20 EXCEL GUIDE 20-27
EG20.1 Payoff Tables and Decision Trees 20-27
EG20.2 Criteria for Decision Making 20-27
Appendices 711
Basic Math Concepts and Symbols 712
A.1 Operators 712
A.2 Rules for Arithmetic Operations 712
A.3 Rules for Algebra: Exponents and Square Roots 712
A.4 Rules for Logarithms 713
A.5 Summation Notation 714
A.6 Greek Alphabet 717
Important Software Skills and Concepts 718
B.1 Identifying the Software Version 718
B.2 Formulas 718
B.3 Excel Cell References 720
B.4 Excel Worksheet Formatting 721
B.5E Excel Chart Formatting 722
B.5J JMP Chart Formatting 723
B.5M Minitab Chart Formatting 724
B.6 Creating Histograms for Discrete Probability
Distributions (Excel) 724
B.7 Deleting the “Extra” Histogram Bar (Excel) 725
Online Resources 726
C.1 About the Online Resources for This Book 726
C.2 Data Files 726
C.3 Files Integrated With Microsoft Excel 733
C.4 Supplemental Files 733
Configuring Software 734
D.1 Microsoft Excel Configuration 734
D.2 JMP Configuration 736
D.3 Minitab Configuration 736
Table 737
E.1 Table of Random Numbers 737
E.2 The Cumulative Standardized Normal
Distribution 739
E.3 Critical Values of t 741
E.4 Critical Values of x2 743
E.5 Critical Values of F 744
E.6 Lower and Upper Critical Values, T1, of the Wilcoxon
Rank Sum Test 748
E.7 Critical Values of the Studentized Range, Q 749
E.8 Critical Values, dL and dU, of the Durbin–Watson
Statistic, D (Critical Values Are One–Sided) 751
E.9 Control Chart Factors 752
E.10 The Standardized Normal Distribution 753
Useful Knowledge 754
F.1 Keyboard Shortcuts 754
F.2 Understanding the Nonstatistical Functions 754
Software FAQs 756
G.1 Microsoft Excel FAQs 756
G.2 PHStat FAQs 756
G.3 JMP FAQs 757
G.4 Minitab FAQs 757
All About PHStat 758
H.1 What is PHStat? 758
H.2 Obtaining and Setting Up PHStat 759
H.3 Using PHStat 759
H.4 PHStat Procedures, by Category 760
Self-Test Solutions and Answers to
Selected Even-Numbered Problems 761
Index 793
Credits 805