## Business Statistics: A First Course, Global Edition

(2016)

### Abstract

Statistics is essential for all business majors, and this text helps students see the role statistics will play in their own careers by providing examples drawn from all functional areas of business. Guided by principles set by major statistical and business science associations (ASA and DSI), plus the authors’ diverse experiences, the Seventh Edition of Levine/Szabat/Stephan’s Business Statistics: A First Course continues to innovate and improve the way this course is taught to all students. This brief version, created to fit the needs of a one-semester course, is part of the established Berenson/Levine series.

MyStatLab not included. Students, if MyStatLab is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN and course ID. MyStatLab should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information.

MyStatLab is an online homework, tutorial, and assessment product designed to personalize learning and improve results. With a wide range of interactive, engaging, and assignable activities, students are encouraged to actively learn and retain tough course concepts.

Section Title Page Action Price
Cover Cover
Dedication 5
Brief Contents 7
Contents 8
Preface 15
Getting Started: Important Things to Learn First 23
Using Statistics: “You Cannot Escape from Data” 23
GS.1 Statistics: A Way of Thinking 24
GS.2 Data: What is it? 24
Statistics 25
GS.3 The Changing Face of Statistics 26
“Big Data” 26
Integral Role of Software in Statistics 27
Making Best Use of This Book 27
Making Best Use of the Software Guides 28
References 29
Key Terms 29
Excel Guide 30
EG.1 Getting Started with Microsoft Excel 30
EG.2 Entering Data 30
Minitab Guide 31
MG.1 Getting Started with Minitab 31
MG.2 Entering Data 31
Chapter 1: Defining and Collecting Data 32
Using Statistics: Beginning of the End … Or the End of the Beginning? 32
1.1 Defining Variables 33
Classifying Variables by Type 33
1.2 Collecting Data 35
Data Sources 35
Populations and Samples 36
Structured Versus Unstructured Data 36
Electronic Formats and Encodings 37
Data Cleaning 37
Recoding Variables 37
1.3 Types of Sampling Methods 38
Simple Random Sample 39
Systematic Sample 40
Stratified Sample 40
Cluster Sample 40
1.4 Types of Survey Errors 41
Coverage Error 42
Nonresponse Error 42
Sampling Error 42
Measurement Error 42
Using Statistics: Beginning of the End… Revisited 44
Summary 45
References 45
Key Terms 45
Chapter Review Problems 46
Cases for Chapter1 47
Managing Ashland MultiComm Services 47
CardioGood Fitness 47
Clear Mountain State Student Surveys 48
Learning with the Digital Cases 48
Chapter 1 Excel Guide 50
EG1.1 Defining Variables 50
EG1.2 Collecting Data 50
EG1.3 Types of Sampling Methods 50
Chapter 1 Minitab Guide 51
MG1.1 Defining Variables 51
MG1.2 Collecting Data 51
MG1.3 Types of Sampling Methods 52
Chapter 2: Organizing and Visualizing Variables 53
Using Statistics: The Choice is Yours 53
2.1 Organizing Categorical Variables 55
The Summary Table 55
The Contingency Table 55
2.2 Organizing Numerical Variables 59
The Ordered Array 59
The Frequency Distribution 60
Classes and Excel Bins 62
The Relative Frequency Distribution and the Percentage Distribution 62
The Cumulative Distribution 64
Stacked and Unstacked Data 66
2.3 Visualizing Categorical Variables 68
The Bar Chart 68
The Pie Chart 69
The Pareto Chart 70
The Side-by-Side Bar Chart 72
2.4 Visualizing Numerical Variables 74
The Stem-and-Leaf Display 74
The Histogram 76
The Percentage Polygon 77
The Cumulative Percentage Polygon (Ogive) 78
2.5 Visualizing Two Numerical Variables 82
The Scatter Plot 82
The Time-Series Plot 83
2.6 Organizing and Visualizing a Set of Variables 85
Multidimensional Contingency Tables 86
Data Discovery 87
2.7 The Challenge in Organizing and Visualizing Variables 89
Obscuring Data 89
Creating False Impressions 90
Chartjunk 90
Best Practices for Constructing Visualizations 92
Using Statistics: The Choice is Yours, Revisited 93
Summary 94
References 94
Key Equations 95
Key Terms 95
Chapter Review Problems 96
Cases for Chapter 2 100
Managing Ashland MultiComm Services 100
Digital Case 101
CardioGood Fitness 101
The Choice is Yours Follow-Up 101
Clear Mountain State Student Surveys 101
Chapter 2 Excel Guide 102
EG2.1 Organizing Categorical Variables 102
EG2.2 Organizing Numerical Variables 104
EG2.3 Visualizing Categorical Variables 106
EG2.4 Visualizing Numerical Variables 108
EG2.5 Visualizing Two Numerical Variables 111
EG2.6 Organizing and Visualizing a Set of Variables 111
Chapter 2 Minitab Guide 113
MG2.1 Organizing Categorical Variables 113
MG2.2 Organizing Numerical Variables 113
MG2.3 Visualizing Categorical Variables 114
MG2.4 Visualizing Numerical Variables 115
MG2.5 Visualizing Two Numerical Variables 117
MG2.6 Organizing and Visualizing a Set of Variables 118
Chapter 3: Numerical Descriptive Measures 119
Using Statistics: More Descriptive Choices 119
3.1 Central Tendency 120
The Mean 120
The Median 122
The Mode 123
3.2 Variation and Shape 124
The Range 124
The Variance and the Standard Deviation 125
The Coefficient of Variation 129
Z Scores 130
Shape: Skewness 131
Shape: Kurtosis 132
3.3 Exploring Numerical Data 135
Quartiles 135
The Interquartile Range 137
The Five-Number Summary 138
The Boxplot 139
3.4 Numerical Descriptive Measures for a Population 142
The Population Mean 142
The Population Variance and Standard Deviation 143
The Empirical Rule 144
The Chebyshev Rule 145
3.5 The Covariance and the Coefficient of Correlation 146
The Covariance 147
The Coefficient of Correlation 148
3.6 Descriptive Statistics: Pitfalls and Ethical Issues 152
Using Statistics: More Descriptive Choices, Revisited 152
Summary 153
References 153
Key Equations 153
Key Terms 154
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 158
Clear Mountain State Student Surveys 158
Chapter 3 Excel Guide 159
EG3.1 Central Tendency 159
EG3.2 Variation and Shape 159
EG3.3 Exploring Numerical Data 160
EG3.4 Numerical Descriptive Measures for a Population 161
EG3.5 The Covariance and the Coefficient of Correlation 161
Chapter 3 Minitab Guide 162
MG3.1 Central Tendency 162
MG3.2 Variation and Shape 162
MG3.3 Exploring Numerical Data 162
MG3.4 Numerical Descriptive Measures for a Population 163
MG3.5 The Covariance and the Coefficient of Correlation 163
Chapter 4: Basic Probability 164
Using Statistics: Possibilities at M&R Electronics World 164
4.1 Basic Probability Concepts 165
Events and Sample Spaces 166
Contingency Tables and Venn Diagrams 168
Simple Probability 168
Joint Probability 169
Marginal Probability 170
4.2 Conditional Probability 174
Computing Conditional Probabilities 174
Decision Trees 176
Independence 178
Multiplication Rules 179
Marginal Probability Using the General Multiplication Rule 180
4.3 Bayes’ Theorem 182
4.4 Counting Rules 187
4.5 Ethical Issues and Probability 190
Using Statistics: Possibilities at M&R Electronics World, Revisited 191
Summary 191
References 191
Key Equations 192
Key Terms 192
Chapter Review Problems 193
Cases for Chapter 4 195
Digital Case 195
CardioGood Fitness 195
Clear Mountain State Student Surveys 195
Chapter 4 Excel Guide 196
EG4.1 Basic Probability Concepts 196
EG4.2 Conditional Probability 196
EG4.3 Bayes’ Theorem 196
EG4.4 Counting Rules 196
Chapter 4 Minitab Guide 197
MG4.1 Basic Probability Concepts 197
MG4.2 Conditional Probability 197
MG4.3 Bayes’ Theorem 197
MG4.4 Counting Rules 197
Chapter 5: Discrete Probability Distributions 198
Using Statistics: Events of Interest at Ricknel Home Centers 198
5.1 The Probability Distribution for a Discrete Variable 199
Expected Value of a Discrete Variable 199
Variance and Standard Deviation of a Discrete Variable 200
5.2 Binomial Distribution 203
5.3 Poisson Distribution 210
Using Statistics: Events of Interest at Ricknel Home Centers, Revisited 214
Summary 214
References 214
Key Equations 214
Key Terms 215
Chapter Review Problems 215
Cases for Chapter 5 217
Managing Ashland MultiComm Services 217
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 Minitab Guide 220
MG5.1 The Probability Distribution for a Discrete Variable 220
MG5.2 B inomial Distribution 220
MG5.3 Poisson Distribution 220
Chapter 6: The Normal Distribution 222
6.1 Continuous Probability Distributions 223
6.2 The Normal Distribution 223
Computing Normal Probabilities 225
Finding X Values 230
Visual Explorations: Exploring the Normal Distribution 234
6.3 Evaluating Normality 236
Comparing Data Characteristics to Theoretical Properties 236
Constructing the Normal Probability Plot 238
Summary 241
References 241
Key Equations 241
Key Terms 241
Chapter Review Problems 242
Cases for Chapter 6 243
Managing Ashland MultiComm Services 243
Digital Case 244
CardioGood Fitness 244
More Descriptive Choices Follow-up 244
Clear Mountain State Student Surveys 244
Chapter 6 Excel Guide 245
EG6.1 Continuous Probability Distributions 245
EG6.2 The Normal Distribution 245
EG6.3 Evaluating Normality 245
Chapter 6 Minitab Guide 246
MG6.1 Continuous Probability Distributions 246
MG6.2 The Normal Distribution 246
MG6.3 Evaluating Normality 246
Chapter 7: Sampling Distributions 248
Using Statistics: Sampling Oxford Cereals 248
7.1 Sampling Distributions 249
7.2 Sampling Distribution of the Mean 249
The Unbiased Property of the Sample Mean 249
Standard Error of the Mean 251
Sampling from Normally Distributed Populations 252
Sampling from Non-normally Distributed Populations—The Central Limit Theorem 255
Visual Explorations: Exploring Sampling Distributions 259
7.3 Sampling Distribution of the Proportion 260
Using Statistics: Sampling Oxford Cereals, Revisited 264
Summary 264
References 264
Key Equations 264
Key Terms 265
Chapter Review Problems 265
Cases for Chapter 7 267
Managing Ashland MultiComm Services 267
Digital Case 267
Chapter 7 Excel Guide 268
EG7.1 Sampling Distributions 268
EG7.2 Sampling Distribution of the Mean 268
EG7.3 Sampling Distribution of the Proportion 268
Chapter 7 Minitab Guide 269
MG7.1 Sampling Distributions 269
MG7.2 Sampling Distribution of the Mean 269
MG7.3 Sampling Distribution of the Proportion 269
Chapter 8: Confidence Interval Estimation 270
Using Statistics: Getting Estimates at Ricknel Home Centers 270
8.1 Confidence Interval Estimate for the Mean (σ Known) 271
Can You Ever Know the Population Standard Deviation? 276
8.2 Confidence Interval Estimate for the Mean (σ Unknown) 277
Student’s t Distribution 277
Properties of the t Distribution 278
The Concept of Degrees of Freedom 279
The Confidence Interval Statement 280
8.3 Confidence Interval Estimate for the Proportion 285
8.4 Determining Sample Size 288
Sample Size Determination for the Mean 288
Sample Size Determination for the Proportion 290
8.5 Confidence Interval Estimation and Ethical Issues 293
8.6 Bootstrapping 294
Using Statistics: Getting Estimates at Ricknel Home Centers, Revisited 294
Summary 294
References 295
Key Equations 295
Key Terms 295
Chapter Review Problems 296
Cases for Chapter 8 299
Managing Ashland MultiComm Services 299
Digital Case 300
Sure Value Convenience Stores 300
CardioGood Fitness 301
More Descriptive Choices Follow-Up 301
Clear Mountain State Student Surveys 301
Chapter 8 Excel Guide 302
EG8.1 Confidence Interval Estimate for the Mean (σ Known 302
EG8.2 Confidence Interval Estimatefor the Mean (σ Unknown) 302
EG8.3 Confidence Interval Estimate for the Proportion 303
EG8.4 Determining Sample Size 303
Chapter 8 Minitab Guide 304
MG8.1 Confidence Interval Estimate for the Mean (σ Known) 304
MG8.2 Confidence Interval Estimate for the Mean (σ Unknown) 304
MG8.3 Confidence Interval Estimate for the Proportion 304
MG8.4 Determining Sample Size 305
Chapter 9: Fundamentals of Hypothesis Testing: One-Sample Tests 306
Using Statistics: Significant Testing at Oxford Cereals 306
9.1 Fundamentals of Hypothesis-Testing Methodology 307
The Null and Alternative Hypotheses 307
The Critical Value of the Test Statistic 308
Regions of Rejection and Nonrejection 309
Risks in Decision Making Using Hypothesis Testing 309
Z Test for the Mean (σ Known) 312
Hypothesis Testing Using the Critical Value Approach 312
Hypothesis Testing Using the p-Value Approach 315
A Connection Between Confidence Interval Estimation and Hypothesis Testing 317
Can You Ever Know the Population Standard Deviation? 318
9.2 t Test of Hypothesis for the Mean (σ Unknown) 319
The Critical Value Approach 320
The p-Value Approach 322
Checking the Normality Assumption 322
9.3 One-Tail Tests 326
The Critical Value Approach 326
The p-Value Approach 327
9.4 Z Test of Hypothesis for the Proportion 330
The Critical Value Approach 331
The p-Value Approach 332
9.5 Potential Hypothesis-Testing Pitfalls and Ethical Issues 334
Statistical Significance Versus Practical Significance 334
Statistical Insignificance Versus Importance 335
Reporting of Findings 335
Ethical Issues 335
Using Statistics: Significant Testing at Oxford Cereals, Revisited 336
Summary 336
References 336
Key Equations 337
Key Terms 337
Chapter Review Problems 337
Cases for Chapter 9 339
Managing Ashland MultiComm Services 339
Digital Case 340
Sure Value Convenience Stores 340
Chapter 9 Excel Guide 341
EG9.1 Fundamentals of Hypothesis-Testing Methodology 341
EG9.2 t Test of Hypothesis for the Mean (σ Unknown) 341
EG9.3 One -Tail Tests 342
EG9.4 Z Test of Hypothesis for the Proportion 342
Chapter 9 Minitab Guide 343
MG9.1 Fundamentals of Hypothesis-Testing Methodology 343
MG9.2 t Test of Hypothesis for the Mean (σ Unknown) 343
MG9.3 One-Tail Tests 343
MG9.4 Z Test of Hypothesis for the Proportion 344
Chapter 10: Two-Sample Tests and One-Way ANOVA 345
Using Statistics: For North Fork, Are There Different Means to the Ends? 345
10.1 Comparing the Means of Two Independent Populations 346
Pooled-Variance t Test for the Difference Between Two Means 346
Confidence Interval Estimate for the Difference Between Two Means 351
t Test for the Difference Between Two Means, Assuming Unequal Variances 352
Do People Really Do This? 352
10.2 Comparing the Means of Two Related Populations 355
Paired t Test 356
Confidence Interval Estimate for the Mean Difference 361
10.3 Comparing the Proportions of Two Independent Populations 363
Z Test for the Difference Between Two Proportions 363
Confidence Interval Estimate for the Difference Between Two Proportions 367
10.4 F Test for the Ratio of Two Variances 369
10.5 One-Way ANOVA 374
F Test for Differences Among More Than Two Means 377
One-Way ANOVA F Test Assumptions 381
Levene Test for Homogeneity of Variance 382
Multiple Comparisons: The Tukey-Kramer Procedure 383
10.6 Effect Size 388
Using Statistics: For North Fork, Are There Different Means to the Ends? Revisited 389
Summary 389
References 390
Key Equations 390
Key Terms 391
Chapter Review Problems 392
Cases for Chapter 10 394
Managing Ashland MultiComm Services 394
Digital Case 395
Sure Value Convenience Stores 395
CardioGood Fitness 396
More Descriptive Choices Follow-Up 396
Clear Mountain State Student Surveys 396
Chapter 10 Excel Guide 398
EG10.1 Comparing the Means of Two Independent Populations 398
EG10.2 Comparing the Means of Two Related Populations 400
EG10.3 Comparing the Proportions of Two Independent Populations 401
EG10.4 F Test for the Ratio of Two Variances 401
EG10.5 One-Way ANOVA 402
Chapter 10 Minitab Guide 405
MG10.1 Comparing the Means of Two Independent Populations 405
MG10.2 Comparing the Means of Two Related Populations 405
MG10.3 Comparing the Proportions of Two Independent Populations 406
MG10.4 F Test for the Ratio of Two Variances 406
MG10.5 One-Way ANOVA 407
Chapter 11: Chi-Square Tests 409
Using Statistics: Avoiding Guesswork About Resort Guests 409
11.1 Chi-Square Test for the Difference Between Two Proportions 410
11.2 Chi-Square Test for Differences Among More Than Two Proportions 417
11.3 Chi-Square Test of Independence 422
Using Statistics: Avoiding Guesswork About Resort Guests, Revisited 427
Summary 428
References 428
Key Equations 429
Key Terms 429
Chapter Review Problems 429
Cases for Chapter 11 431
Managing Ashland MultiComm Services 431
Digital Case 432
CardioGood Fitness 432
Clear Mountain State Student Surveys 433
Chapter 11 Excel Guide 434
EG11.1 Chi-Square Test for the Difference Between Two Proportions 434
EG11.2 Chi-Square Test for Differences Among More Than Two Proportions 434
EG11.3 Chi-Square Test of Independence 434
Chapter 11 Minitab Guide 435
MG11.1 Chi-Square Test for the Difference Between Two Proportions 435
MG11.2 Chi-Square Test for Differences Among More Than Two Proportions 435
MG11.3 Chi-Square Test of Independence 435
Chapter 12: Simple Linear Regression 436
Using Statistics: Knowing Customers at Sunflowers Apparel 436
12.1 Types of Regression Models 437
Simple Linear Regression Models 438
12.2 Determining the Simple Linear Regression Equation 439
The Least-Squares Method 439
Predictions in Regression Analysis: Interpolation Versus Extrapolation 442
Computing the Y Intercept, b0, and the Slope, b1 442
Visual Explorations: Exploring Simple Linear Regression Coefficients 445
12.3 Measures of Variation 447
Computing the Sum of Squares 447
The Coefficient of Determination 448
Standard Error of the Estimate 450
12.4 Assumptions of Regression 452
12.5 Residual Analysis 452
Evaluating the Assumptions 452
12.6 Measuring Autocorrelation: The Durbin-Watson Statistic 456
Residual Plots to Detect Autocorrelation 456
The Durbin-Watson Statistic 457
12.7 Inferences About the Slope and Correlation Coefficient 460
t Test for the Slope 460
F Test for the Slope 462
Confidence Interval Estimate for the Slope 463
t Test for the Correlation Coefficient 464
12.8 Estimation of Mean Values and Prediction of Individual Values 467
The Confidence Interval Estimate for the Mean Response 467
The Prediction Interval for an Individual Response 468
12.9 Potential Pitfalls in Regression 471
Six Steps for Avoiding the Potential Pitfalls 473
Using Statistics: Knowing Customers at Sunflowers Apparel, Revisited 473
Summary 473
References 474
Key Equations 475
Key Terms 476
Chapter Review Problems 476
Cases for Chapter 12 480
Managing Ashland MultiComm Services 480
Digital Case 480
Brynne Packaging 480
Chapter 12 Excel Guide 482
EG12.1 Types of Regression Models 482
EG12.2 Determining the Simple Linear Regression Equation 482
EG12.3 Measures of Variation 483
EG12.4 Assumptions of Regression 483
EG12.5 Residual Analysis 483
EG12.6 Measuring Autocorrelation: the Durbin-Watson Statistic 484
EG12.7 Inferences About the Slope and Correlation Coefficient 484
EG 12.8 Estimation of Mean Values and Prediction of Individual Values 484
Chapter 12 Minitab Guide 484
MG12.1 Types of Regression Models 484
MG12.2 Determining the Simple Linear Regression Equation 484
MG12.3 Measures of Variation 485
MG12.4 Assumptions 485
MG12.5 Residual Analysis 485
MG12.6 Measuring Autocorrelation: the Durbin-Watson Statistic 485
MG12.7 Inferences About the Slope and Correlation Coefficient 485
MG12.8 Estimation of Mean Values and Prediction of Individual Values 485
Chapter 13: Multiple Regression 486
Using Statistics: The Multiple Effects of OmniPower Bars 486
13.1 Developing a Multiple Regression Model 487
Interpreting the Regression Coefficients 488
Predicting the Dependent Variable Y 490
13.2 r2, Adjusted r2, and the Overall F Test 492
Coefficient of Multiple Determination 492
Test for the Significance of the Overall Multiple Regression Model 494
13.3 Residual Analysis for the Multiple Regression Model 496
13.4 Inferences Concerning the Population Regression Coefficients 497
Tests of Hypothesis 497
Confidence Interval Estimation 499
13.5 Using Dummy Variables and Interaction Terms in Regression Models 501
Dummy Variables 501
Interactions 503
Using Statistics: The Multiple Effects of OmniPower Bars, Revisited 507
Summary 507
References 507
Key Equations 509
Key Terms 509
Chapter Review Problems 509
Cases for Chapter 13 512
Managing Ashland MultiComm Services 512
Digital Case 512
Chapter13 Excel Guide 513
EG13.1 Developing a Multiple Regression Model 513
EG13.2 r2, Adjusted r2, and the Overall F Test 514
EG13.3 Residual Analysis for the Multiple Regression Model 514
EG13.4 Inferences Concerning the Population Regression Coefficients 515
EG13.5 Using Dummy Variables and Interaction Terms in Regression Models 515
Chapter 13 Minitab Guide 515
MG13.1 Developing a Multiple Regression Model 515
MG13.2 r2, Adjusted r2, and the Overall F Test 516
MG13.3 Residual Analysis for the Multiple Regression Model 516
MG13.4 Inferences Concerning the Population Regression Coefficients 516
MG13.5 Using Dummy Variables and Interaction Terms in Regression Models 517
Chapter 14: Statistical Applications in Quality Management 14-1
Using Statistics: Finding Quality at the Beachcomber 14-1
14.1 The Theory of Control Charts 14-2
14.2 Control Chart for the Proportion: The p Chart 14-4
14.3 The Red Bead Experiment: Understanding Process Variability 14-10
14.4 Control Chart for an Area of Opportunity: The c Chart 14-12
14.5 Control Charts for the Range and the Mean 14-15
The R Chart 14-16
The X—Chart 14-18
14.6 Process Capability 14-21
Customer Satisfaction and Specification Limits 14-21
Capability Indices 14-23
CPL, CPU, and Cpk 14-24
14.7 Total Quality Management 14-26
14.8 Six Sigma 14-28
The DMAIC Model 14-29
Roles in a Six Sigma Organization 14-30
Lean Six Sigma 14-30
Using Statistics: Finding Quality at the Beachcomber, Revisited 14-31
Summary 14-31
References 14-32
Key Equations 14-32
Key Terms 14-33
Chapter Review Problems 14-34
The Harnswell Sewing Machine Company Case 14-36
Managing Ashland Multicomm Services 14-38
Chapter 14 Excel Guide 14-39
EG14.1 The Theory of Control Charts 14-39
EG14.2 Control Chart for the Proportion: The p Chart 14-39
EG14.3 The Red Bead Experiment: Understanding Process Variability 14-40
EG14.4 Control Chart for an Area of Opportunity: The c Chart 14-40
EG14.5 Control Charts for the Range and the Mean 14-41
EG14.6 Process Capability 14-42
Chapter 14 Minitab Guide 14-42
MG14.1 The Theory of Control Charts 14-42
MG14.2 Control Chart for the Proportion: the p Chart 14-42
MG14.3 The Red Bead Experiment: Understanding Process Variability 14-42
MG14.4 Control Chart for an Area of Opportunity: the c Chart 14-42
MG14.5 Control Charts for the Range and the Mean 14-43
MG14.6 Process Capability 14-44
Appendices 518
Appendix A: Basic Math Concepts and Symbols 519
A.1 Rules for Arithmetic Operations 519
A.2 Rules for Algebra: Exponents and Square Roots 519
A.3 Rules for Logarithms 520
A.4 Summation Notation 521
A.5 Statistical Symbols 524
A.6 Greek Alphabet 524
Appendix B: Important Excel and Minitab Skills 525
B.1 Basic Excel Operations 525
B.2 Formulas and Cell References 525
B.3 Entering Formulas into Worksheets 526
B.4 Pasting with Paste Special 527
B.5 Basic Worksheet Cell Formatting 527
B.6 Chart Formatting 529
B.7 Selecting Cell Ranges for Charts 530
B.8 Deleting the “Extra” Histogram Bar 530
B.9 Creating Histograms for Discrete Probability Distributions 530
B.10 Basic Minitab Operations 531
Appendix C: Online Resources 532
C.1 About the Online Resources for This Book 532
C.2 Accessing the Online Resources 532
C.4 PHStat 537
Appendix D: Configuring Microsoft Excel 538
D.1 Getting Microsoft Excel Ready for Use (ALL) 538
D.2 Getting PHStat Ready for Use (ALL) 539
D.3 Configuring Excel Security for Add-In Usage (WIN) 539
D.4 Opening PHStat (ALL) 540
D.5 Using a Visual Explorations Add-In Workbook (ALL) 540
D.6 Checking for the Presence of the Analysis ToolPak (ALL) 540
Appendix E: Tables 541
E.1 Table of Random Numbers 541
E.2 The Cumulative Standardized Normal Distribution 543
E.3 Critical Values of t 545
E.4 Critical Values of x2 547
E.5 Critical Values of F 548
E.6 Critical Values of the Studentized Range, Q 552
E.7 Critical Values, dL and dU, of the Durbin-Watson Statistic, D (Critical Values Are One-Sided) 554
E.8 Control Chart Factors 555
E.9 The Standardized Normal Distribution 556
Appendix F: Useful Excel Knowledge 557
F.1 Useful Keyboard Shortcuts 557
F.2 Verifying Formulas and Worksheets 557
F.3 New Function Names 558
F.4 Understanding the Nonstatistical Functions 559
Appendix G: Software FAQs 561
G.1 PHStat FAQs 561
G.2 Microsoft Excel FAQs 562
G.3 FAQs for New Users of Microsoft Excel 2013 562
G.4 Minitab FAQs 563
Self-Test Solutions and Answers to Selected Even-Numbered Problems 564
Index 589