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					                                   A ROADMAP FOR SELECTING
                                     A STATISTICAL METHOD



                                                                    TYPE OF DATA
Type of Analysis                               Numerical                                      Categorical
Describing a group          Ordered array, stem-and-leaf display, frequency        Summary table, bar chart, pie
or several groups           distribution, relative frequency distribution,         chart, Pareto chart (Sections 2.2, 2.4)
                            percentage distribution, cumulative percentage
                            distribution, histogram, polygon, cumulative
                            percentage polygon (Sections 2.3, 2.5)
                            Mean, median, mode, quartiles, geometric mean,
                            range, interquartile range, standard deviation,
                            variance, coefficient of variation, boxplot
                            (Sections 3.1, 3.2, 3.3)
                            Index numbers (Online Topic 16.8)

Inference about one group   Confidence interval estimate of the mean               Confidence interval estimate of the
                            (Sections 8.1 and 8.2)                                 proportion (Section 8.3)
                            t test for the mean (Section 9.2)                      Z test for the proportion
                            Chi-square test for a variance (Section 12.5)          (Section 9.4)

Comparing two groups        Tests for the difference in the means of two           Z test for the difference between
                            independent populations (Section 10.1)                 two proportions (Section 10.3)
                            Paired t test (Section 10.2)                           Chi-square test for the difference
                            F test for the difference between two variances        between two proportions
                            (Section 10.4)                                         (Section 12.1)
                            Wilcoxon rank sum test (Section 12.6)                  McNemar test for the difference
                            Wilcoxon signed ranks test (Online Topic 12.8)         between two proportions in related
                                                                                   samples (Section 12.4)

Comparing more              One-way analysis of variance (Section 11.1)            Chi-square test for differences
than two groups             Randomized block design (Section 11.2)                 among more than two proportions
                            Two-way analysis of variance (Section 11.3)            (Section 12.2)
                            Kruskal-Wallis test (Section 12.7)
                            Friedman rank test (Online Topic 12.9)

Analyzing the               Scatter plot, time series plot (Section 2.6)           Contingency table, side-by-side
relationship between        Covariance, coefficient of correlation (Section 3.5)   bar chart, (Sections 2.2, 2.4)
two variables               Simple linear regression (Chapter 13)                  Chi-square test of independence
                            t test of correlation (Section 13.7)                   (Section 12.3)
                            Time series forecasting (Chapter 16)

Analyzing the               Multiple regression (Chapters 14 and 15)               Multidimensional contingency
relationship between                                                               tables (Section 2.7)
two or more variables                                                              Logistic regression (Section 14.7)
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     Basic Business
Statistics: Concepts and
      Applications
         TWELFTH EDITION
      Basic Business
 Statistics: Concepts and
       Applications
                                      TWELFTH EDITION




                Mark L. Berenson
                Department of Management and Information Systems

                School of Business, Montclair State University



                David M. Levine
                Department of Statistics and Computer Information Systems

                Zicklin School of Business, Baruch College, City University of New York



                Timothy C. Krehbiel
                Department of Management

                Richard T. Farmer School of Business, Miami University




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                                                                                      10 9 8 7 6 5 4 3 2 1
                                                                                      ISBN 10: 0-13-216838-3
                                                                                   ISBN 13: 978-0-13-216838-0
             To our wives,
   Rhoda B., Marilyn L., and, Patti K.,

            and to our children,
Kathy, Lori, Sharyn, Ed, Rudy, and Rhonda
About the Authors




                         The textbook authors meet to discuss statistics at a Mets
                         baseball game. Shown left to right: David Levine, Mark
                                     Berenson, and Tim Krehbiel.


          Mark L. Berenson is Professor of Management and Information Systems at
          Montclair State University (Montclair, New Jersey) and also Professor Emeritus of
          Statistics and Computer Information Systems at Bernard M. Baruch College (City
          University of New York). He currently teaches graduate and undergraduate courses in sta-
          tistics and in operations management in the School of Business and an undergraduate
          course in international justice and human rights that he co-developed in the College of
          Humanities and Social Sciences.
          Berenson received a B.A. in economic statistics and an M.B.A. in business statistics from
          City College of New York and a Ph.D. in business from the City University of New York.
          Berenson’s research has been published in Decision Sciences Journal of Innovative
          Education, Review of Business Research, The American Statistician, Communications in
          Statistics, Psychometrika, Educational and Psychological Measurement, Journal of
          Management Sciences and Applied Cybernetics, Research Quarterly, Stats Magazine, The
          New York Statistician, Journal of Health Administration Education, Journal of Behavioral
          Medicine, and Journal of Surgical Oncology. His invited articles have appeared in The
          Encyclopedia of Measurement & Statistics and Encyclopedia of Statistical Sciences. He is
          co-author of 11 statistics texts published by Prentice Hall, including Statistics for
          Managers Using Microsoft Excel, Basic Business Statistics: Concepts and Applications,
          and Business Statistics: A First Course.
          Over the years, Berenson has received several awards for teaching and for innovative con-
          tributions to statistics education. In 2005, he was the first recipient of The Catherine A.
          Becker Service for Educational Excellence Award at Montclair State University.


          David M. Levine                 is Professor Emeritus of Statistics and Computer Infor-
          mation Systems at Baruch College (City University of New York). He received B.B.A. and
          M.B.A. degrees in Statistics from City College of New York and a Ph.D. from New York
viii
                                                                                              ABOUT THE AUTHORS   ix




University in Industrial Engineering and Operations Research. He is nationally recognized
as a leading innovator in statistics education and is the co-author of 14 books, including
such best-selling statistics textbooks as Statistics for Managers Using Microsoft Excel,
Basic Business Statistics: Concepts and Applications, Business Statistics: A First Course,
and Applied Statistics for Engineers and Scientists Using Microsoft Excel and Minitab.
 He also is the co-author of Even You Can Learn Statistics: A Guide for Everyone Who Has
Ever Been Afraid of Statistics, currently in its 2nd edition, Six Sigma for Green Belts and
Champions and Design for Six Sigma for Green Belts and Champions, and the author of
Statistics for Six Sigma Green Belts, all published by FT Press, a Pearson imprint, and
Quality Management, 3rd edition, McGraw-Hill/Irwin. He is also the author of Video
Review of Statistics and Video Review of Probability, both published by Video Aided
Instruction, and the statistics module of the MBA primer published by Cengage Learning.
He has published articles in various journals, including Psychometrika, The American
Statistician, Communications in Statistics, Decision Sciences Journal of Innovative
Education, Multivariate Behavioral Research, Journal of Systems Management, Quality
Progress, and The American Anthropologist, and given numerous talks at the Decision
Sciences Institute (DSI), American Statistical Association (ASA), and Making Statistics
More Effective in Schools and Business (MSMESB) conferences. Levine has also received
several awards for outstanding teaching and curriculum development from Baruch College.


Timothy C. Krehbiel                  is Professor of Management and Senior Associate
Dean of the Farmer School of Business at Miami University in Oxford, Ohio. He teaches
undergraduate and graduate courses in business statistics. In 1996, he received the presti-
gious Instructional Innovation Award from the Decision Sciences Institute. He has also
received the Farmer School of Business Effective Educator Award and has twice been
named MBA professor of the year.
Krehbiel’s research interests span many areas of business and applied statistics. His work
has appeared in numerous journals, including Quality Management Journal, Ecological
Economics, International Journal of Production Research, Journal of Purchasing and
Supply Management, Journal of Applied Business Research, Journal of Marketing
Management, Communications in Statistics, Decision Sciences Journal of Innovative
Education, Journal of Education for Business, Marketing Education Review, Journal of
Accounting Education, and Teaching Statistics. He is a co-author of three statistics text-
books published by Prentice Hall: Business Statistics: A First Course, Basic Business
Statistics, and Statistics for Managers Using Microsoft Excel. Krehbiel is also a co-author
of the book Sustainability Perspectives in Business and Resources.
Krehbiel graduated summa cum laude with a B.A. in history from McPherson College and
earned an M.S. and a Ph.D. in statistics from the University of Wyoming.
Brief Contents
Preface xxiii
 1 Introduction 2
 2 Organizing and Visualizing Data 26
 3 Numerical Descriptive Measures 94
 4 Basic Probability 144
 5 Discrete Probability Distributions 180
 6 The Normal Distribution and Other Continuous Distributions 216
 7 Sampling and Sampling Distributions 248
 8 Confidence Interval Estimation 278
 9 Fundamentals of Hypothesis Testing: One-Sample Tests 324
10 Two-Sample Tests 364
11 Analysis of Variance 414
12 Chi-Square Tests and Nonparametric Tests 466
13 Simple Linear Regression 520
14 Introduction to Multiple Regression 576
15 Multiple Regression Model Building 628
16 Time-Series Forecasting 664
17 Statistical Applications in Quality Management 716
18 A Road Map for Analyzing Data 762
    Online Chapter: 19 Decision Making
Appendices A–G 773
Self-Test Solutions and Answers to Selected Even-Numbered Problems 820
Index 850




                                                                         xi
Contents
      Preface xxiii                                            ORGANIZING DATA 29
                                                               2.2   Organizing Categorical Data 30
                                                                       The Summary Table 30
                                                                       The Contingency Table 30

1 Introduction                                            2    2.3   Organizing Numerical Data 33
                                                                       Stacked and Unstacked Data 33
USING STATISTICS @ Good Tunes & More 3                                 The Ordered Array 34
                                                                       The Frequency Distribution 35
1.1    Why Learn Statistics 4
                                                                       The Relative Frequency Distribution and the Percentage
1.2    Statistics in Business 4                                        Distribution 37
1.3    Basic Vocabulary of Statistics 5                                The Cumulative Distribution 38
1.4    Identifying Type of Variables 7                         VISUALIZING DATA 41
         Measurement Scales 7                                  2.4   Visualizing Categorical Data 41
1.5    Statistical Applications for Desktop                            The Bar Chart 42
       Computing 10                                                    The Pie Chart 43
1.6    How to Use This Book 11                                         The Pareto Chart 44
         Checklist for Getting Started 11                              The Side-by-Side Bar Chart 46
USING STATISTICS @ Good Tunes & More Revisited 13              2.5   Visualizing Numerical Data 49
       SUMMARY 13                                                      The Stem-and-Leaf Display 49
       KEY TERMS 13                                                    The Histogram 50
       CHAPTER REVIEW PROBLEMS 13
                                                                       The Percentage Polygon 51
                                                                       The Cumulative Percentage Polygon (Ogive) 53
       END-OF-CHAPTER CASES 15
       LEARNING WITH THE DIGITAL CASES 15
                                                               2.6   Visualizing Two Numerical Variables 56
                                                                       The Scatter Plot 56
       REFERENCES 16
                                                                       The Time-Series Plot 58
       CHAPTER 1 EXCEL GUIDE 17
                                                               2.7   Organizing Multidimensional Data 60
         EG1.1 Getting Started with Excel 17
                                                                       Multidimensional Contingency Tables 60
         EG1.2 Entering Data and Variable Type 18
                                                                       Adding Numerical Variables 61
         EG1.3 Opening and Saving Workbooks 18
         EG1.4 Creating and Copying Worksheets 19              2.8 Misuses and Common Errors in Visualizing Data 63
         EG1.5 Printing Worksheets 19                          USING STATISTICS @ Choice Is Yours, Part I Revisited 66
         EG1.6 Worksheet Entries and References 20                   SUMMARY 67
         EG1.7 Absolute and Relative Cell References 21              KEY EQUATIONS 67
         EG1.8 Entering Formulas into Worksheets 21                  KEY TERMS 68
         EG1.9 Using Appendices D and F 21                           CHAPTER REVIEW PROBLEMS 68
       CHAPTER 1 MINITAB GUIDE 22                                    MANAGING ASHLAND MULTICOMM SERVICES 74
         MG1.1 Getting Started With Minitab 22                       DIGITAL CASE 75
         MG1.2 Entering Data and Variable Type 22                    REFERENCES 75
         MG1.3 Opening and Saving Worksheets and                     CHAPTER 2 EXCEL GUIDE 76
         Projects 23                                                   EG2.2 Organizing Categorical Data 76
         MG1.4 Creating and Copying Worksheets 24                      EG2.3 Organizing Numerical Data 78
         MG1.5 Printing Parts of a Project 24                          EG2.4 Visualizing Categorical Data 80
         MG1.6 Worksheet Entries and References 24                     EG2.5 Visualizing Numerical Data 82
         MG1.7 Using Appendices D and F 25                             EG2.6 Visualizing Two Numerical Variables 84
                                                                       EG2.7 Organizing Multidimensional Data 85
                                                                     CHAPTER 2 MINITAB GUIDE 87
2 Organizing and Visualizing                                           MG2.2 Organizing Categorical Data 87
                                                                       MG2.3 Organizing Numerical Data 87
      Data                                                26           MG2.4 Visualizing Categorical Data 88
                                                                       MG2.5 Visualizing Numerical Data 89
USING STATISTICS @ Choice Is Yours, Part I 27                          MG2.6 Visualizing Two Numerical Variables 92
2.1    Data Collection 28                                              MG2.7 Organizing Multidimensional Data 93
                                                                                                                                xiii
xiv     CONTENTS


3 Numerical Descriptive                                           4 Basic Probability                                        144
      Measures                                               94   USING STATISTICS @ M&R Electronics World 145
                                                                  4.1   Basic Probability Concepts 146
USING STATISTICS @ Choice Is Yours, Part II 95
                                                                          Events and Sample Spaces 147
3.1   Central Tendency 96                                                 Contingency Tables and Venn Diagrams 148
        The Mean 96
                                                                          Simple Probability 149
        The Median 98
                                                                          Joint Probability 150
        The Mode 99
                                                                          Marginal Probability 150
        The Geometric Mean 100
                                                                          General Addition Rule 151
3.2   Variation and Shape 101
                                                                  4.2   Conditional Probability 155
      The Range 102
      The Variance and the Standard Deviation 102                         Computing Conditional Probabilities 155
      The Coefficient of Variation 106                                    Decision Trees 156
      Z Scores 107                                                        Independence 158
      Shape 108                                                           Multiplication Rules 159
VISUAL EXPLORATIONS: Exploring Descriptive                                Marginal Probability Using the General Multiplication
    Statistics 110                                                        Rule 160
3.3   Exploring Numerical Data 113                                4.3   Bayes’ Theorem 163
        Quartiles 113                                             THINK ABOUT THIS: Divine Providence and Spam 166
        The Interquartile Range 115                               4.4 Counting Rules 167
        The Five-Number Summary 115                                     Counting Rule 1 167
        The Boxplot 117                                                 Counting Rule 2 168
3.4   Numerical Descriptive Measures for a Population 120               Counting Rule 3 168
        The Population Mean 121                                         Counting Rule 4 169
        The Population Variance and Standard Deviation 121              Counting Rule 5 169
        The Empirical Rule 122                                    4.5 Ethical Issues and Probability 171
        The Chebyshev Rule 123
                                                                  USING STATISTICS @ M&R Electronics World Revisited 172
3.5   The Covariance and the Coefficient of                             SUMMARY 172
      Correlation 125
                                                                        KEY EQUATIONS 172
        The Covariance 125
                                                                        KEY TERMS 173
        The Coefficient of Correlation 127
                                                                        CHAPTER REVIEW PROBLEMS 173
3.6 Descriptive Statistics: Pitfalls and Ethical Issues 131
                                                                        DIGITAL CASE 175
USING STATISTICS @ Choice Is Yours, Part II Revisited 131
                                                                        REFERENCES 176
      SUMMARY 132
                                                                        CHAPTER 4 EXCEL GUIDE 177
      KEY EQUATIONS 132
                                                                          EG4.1 Basic Probability Concepts 177
      KEY TERMS 133                                                       EG4.2 Conditional Probability 177
      CHAPTER REVIEW PROBLEMS 133                                         EG4.3 Bayes’ Theorem 177
      MANAGING ASHLAND MULTICOMM SERVICES 138                             EG4.4 Counting Rules 178
      DIGITAL CASE 138                                                  CHAPTER 4 MINITAB GUIDE 178
      REFERENCES 138                                                      MG4.1 Basic Probability Concepts 178
      CHAPTER 3 EXCEL GUIDE 139                                           MG4.2 Conditional Probability 178
        EG3.1 Central Tendency 139                                        MG4.3 Bayes’ Theorem 178
        EG3.2 Variation and Shape 139                                     MG4.4 Counting Rules 178
        EG3.3 Exploring Numerical Data 140
        EG3.4 Numerical Descriptive Measures for a
        Population 140
        EG3.5 The Covariance and the Coefficient of
        Correlation 141
                                                                  5 Discrete Probability
      CHAPTER 3 MINITAB GUIDE 141                                       Distributions                                        180
        MG3.1 Central Tendency 141
        MG3.2 Variation and Shape 142                             USING STATISTICS @ Saxon Home Improvement 181
        MG3.3 Exploring Numerical Data 142                        5.1   The Probability Distribution for a Discrete Random
        MG3.4 Numerical Descriptive Measures for a                      Variable 182
        Population 143                                                    Expected Value of a Discrete Random Variable 182
        MG3.5 The Covariance and the Coefficient of                       Variance and Standard Deviation of a Discrete Random
        Correlation 143                                                   Variable 183
                                                                                                             CONTENTS        xv

5.2   Covariance and Its Application in Finance 185                USING STATISTICS @ OurCampus! Revisited 240
        Covariance 185                                                   SUMMARY 240
        Expected Value, Variance, and Standard Deviation of the          KEY EQUATIONS 241
        Sum of Two Random Variables 187
                                                                         KEY TERMS 241
        Portfolio Expected Return and Portfolio Risk 187
                                                                         CHAPTER REVIEW PROBLEMS 241
5.3   Binomial Distribution 190                                          MANAGING ASHLAND MULTICOMM SERVICES 244
5.4   Poisson Distribution 197                                           DIGITAL CASE 244
5.5   Hypergeometric Distribution 201                                    REFERENCES 244
5.6       Online Topic Using the Poisson Distribution                    CHAPTER 6 EXCEL GUIDE 245
      to Approximate the Binomial Distribution 204                         EG6.1 Continuous Probability Distributions 245
USING STATISTICS @ Saxon Home Improvement                                  EG6.2 The Normal Distribution 245
      Revisited 205                                                        EG6.3 Evaluating Normality 245
      SUMMARY 205                                                          EG6.4 The Uniform Distribution 246
      KEY EQUATIONS 205                                                    EG6.5 The Exponential Distribution 246
      KEY TERMS 206                                                      CHAPTER 6 MINITAB GUIDE 246
      CHAPTER REVIEW PROBLEMS 206                                          MG6.1 Continuous Probability Distributions 246
      MANAGING ASHLAND MULTICOMM SERVICES 209
                                                                           MG6.2 The Normal Distribution 246
                                                                           MG6.3 Evaluating Normality 247
      DIGITAL CASE 210
                                                                           MG6.4 The Uniform Distribution 247
      REFERENCES 210
                                                                           MG6.5 The Exponential Distribution 247
      CHAPTER 5 EXCEL GUIDE 211
        EG5.1 The Probability Distribution for a Discrete Random
        Variable 211
        EG5.2 Covariance and Its Application in Finance 211
        EG5.3 Binomial Distribution 212
                                                                   7 Sampling and Sampling
        EG5.4 Poisson Distribution 212                                   Distributions                                      248
        EG5.5 Hypergeometric Distribution 213
                                                                   USING STATISTICS @ Oxford Cereals 249
      CHAPTER 5 MINITAB GUIDE 214
        MG5.1 The Probability Distribution for a Discrete Random   7.1   Types of Sampling Methods 250
        Variable 214                                                       Simple Random Samples 251
        MG5.2 Covariance and Its Application in Finance 214                Systematic Samples 253
        MG5.3 Binomial Distribution 214                                    Stratified Samples 253
        MG5.4 Poisson Distribution 214                                     Cluster Samples 254
        MG5.5 Hypergeometric Distribution 215                      7.2   Evaluating Survey Worthiness 255
                                                                           Survey Error 255
                                                                           Ethical Issues 256
                                                                   THINK ABOUT THIS: New Media Surveys/Old Sampling
6 The Normal Distribution                                          7.3
                                                                       Problem 256
                                                                         Sampling Distributions 258
      and Other Continuous                                         7.4   Sampling Distribution of the Mean 258
                                                                          The Unbiased Property of the Sample Mean 258
      Distributions                                        216            Standard Error of the Mean 260
USING STATISTICS @ OurCampus! 217                                         Sampling from Normally Distributed Populations 261
                                                                          Sampling from Non-Normally Distributed Populations—
6.1   Continuous Probability Distributions 218                            The Central Limit Theorem 264
6.2   The Normal Distribution 218                                  VISUAL EXPLORATIONS: Exploring Sampling Distributions 265
       Computing Normal Probabilities 220                          7.5 Sampling Distribution of the Proportion 266
THINK ABOUT THIS: What Is Normal? 228
                                                                   7.6     Online Topic: Sampling from Finite
VISUAL EXPLORATIONS: Exploring the Normal
                                                                       Populations 269
     Distribution 229
6.3   Evaluating Normality 230                                     USING STATISTICS @ Oxford Cereals Revisited 270
        Comparing Data Characteristics to Theoretical                    SUMMARY 270
        Properties 231                                                   KEY EQUATIONS 270
        Constructing the Normal Probability Plot 232                     KEY TERMS 271
6.4   The Uniform Distribution 235                                       CHAPTER REVIEW PROBLEMS 271
6.5   The Exponential Distribution 237                                   MANAGING ASHLAND MULTICOMM SERVICES 273
6.6       Online Topic: The Normal Approximation to the                  DIGITAL CASE 273
      Binomial Distribution 240                                          REFERENCES 274
xvi      CONTENTS

      CHAPTER 7 EXCEL GUIDE 275                                           CHAPTER 8 MINITAB GUIDE 322
        EG7.1 Types of Sampling Methods 275                                 MG8.1 Confidence Interval Estimate for the
        EG7.2 Evaluating Survey Worthiness 275                              Mean (s Known) 322
        EG7.3 Sampling Distributions 275                                    MG8.2 Confidence Interval Estimate for the
        EG7.4 Sampling Distribution of the Mean 275                         Mean (s Unknown) 323
        EG7.5 Sampling Distribution of the Proportion 276                   MG8.3 Confidence Interval Estimate for the Proportion 323
                                                                            MG8.4 Determining Sample Size 323
      CHAPTER 7 MINITAB GUIDE 276
                                                                            MG8.5 Applications of Confidence Interval Estimation
        MG7.1 Types of Sampling Methods 276                                 in Auditing 323
        MG7.2 Evaluating Survey Worthiness 277
        MG7.3 Sampling Distributions 277
        MG7.4 Sampling Distribution of the Mean 277                 9 Fundamentals of Hypothesis
                                                                          Testing: One-Sample Tests 324
8 Confidence Interval                                               USING STATISTICS @ Oxford Cereals, Part II 325
      Estimation                                            278     9.1   Fundamentals of Hypothesis-Testing Methodology 326
                                                                            The Null and Alternative Hypotheses 326
USING STATISTICS @ Saxon Home Improvement 279                               The Critical Value of the Test Statistic 327
8.1   Confidence Interval Estimate for the Mean                             Regions of Rejection and Nonrejection 328
      (s Known) 280                                                         Risks in Decision Making Using Hypothesis Testing 328
        Can You Ever Know the Population Standard                           Hypothesis Testing Using the Critical Value Approach 331
        Deviation? 285                                                      Hypothesis Testing Using the p-Value Approach 333
8.2   Confidence Interval Estimate for the                                  A Connection Between Confidence Interval Estimation and
      Mean (s Unknown) 286                                                  Hypothesis Testing 336
        Student’s t Distribution 286                                        Can You Ever Know the Population Standard Deviation? 336
        Properties of the t Distribution 287                        9.2   t Test of Hypothesis for the Mean (s Unknown) 338
        The Concept of Degrees of Freedom 288                                The Critical Value Approach 338
        The Confidence Interval Statement 288                                The p-Value Approach 340
8.3   Confidence Interval Estimate for the Proportion 294                    Checking the Normality Assumption 340
8.4   Determining Sample Size 297                                   9.3   One-Tail Tests 344
        Sample Size Determination for the Mean 297                           The Critical Value Approach 345
        Sample Size Determination for the Proportion 299                     The p-Value Approach 346
8.5   Applications of Confidence Interval Estimation in             9.4   Z Test of Hypothesis for the Proportion 349
      Auditing 303                                                           The Critical Value Approach 350
        Estimating the Population Total Amount 304                           The p-Value Approach 351
        Difference Estimation 305                                   9.5   Potential Hypothesis-Testing Pitfalls and Ethical Issues 353
        One-Sided Confidence Interval Estimation of the Rate of             Statistical Significance Versus Practical Significance 353
        Noncompliance with Internal Controls 308                            Reporting of Findings 353
8.6 Confidence Interval Estimation and Ethical Issues 310                   Ethical Issues 354
8.7     Online Topic: Estimation and Sample Size                    9.6     Online Topic: The Power of a Test 354
    Determination for Finite Populations 311
                                                                    USING STATISTICS @ Oxford Cereals, Part II Revisited 354
USING STATISTICS @ Saxon Home Improvement                                 SUMMARY 355
    Revisited 311
                                                                          KEY EQUATIONS 355
      SUMMARY 311
                                                                          KEY TERMS 355
      KEY EQUATIONS 312
                                                                          CHAPTER REVIEW PROBLEMS 355
      KEY TERMS 313
                                                                          MANAGING ASHLAND MULTICOMM SERVICES 358
      CHAPTER REVIEW PROBLEMS 313
                                                                          DIGITAL CASE 358
      MANAGING ASHLAND MULTICOMM SERVICES 317
                                                                          REFERENCES 358
      DIGITAL CASE 318
                                                                          CHAPTER 9 EXCEL GUIDE 359
      REFERENCES 318
                                                                            EG9.1 Fundamentals of Hypothesis-Testing Methodology 359
      CHAPTER 8 EXCEL GUIDE 319
                                                                            EG9.2 t Test of Hypothesis for the Mean (s Unknown) 359
        EG8.1 Confidence Interval Estimate for the                          EG9.3 One-Tail Tests 360
        Mean (s Known) 319
                                                                            EG9.4 Z Test of Hypothesis for the Proportion 361
        EG8.2 Confidence Interval Estimate for the
        Mean (s Unknown) 319                                              CHAPTER 9 MINITAB GUIDE 362
        EG8.3 Confidence Interval Estimate for the Proportion 320           MG9.1 Fundamentals of Hypothesis-Testing Methodology 362
        EG8.4 Determining Sample Size 320                                   MG9.2 t Test of Hypothesis for the Mean (s Unknown) 362
        EG8.5 Applications of Confidence Interval Estimation in             MG9.3 One-Tail Tests 362
        Auditing 321                                                        MG9.4 Z Test of Hypothesis for the Proportion 363
                                                                                                             CONTENTS        xvii

10 Two-Sample Tests                                        364    11.2 The Randomized Block Design 430
                                                                         Testing for Factor and Block Effects 430
                                                                         Multiple Comparisons: The Tukey Procedure 436
USING STATISTICS @ BLK Beverages 365
                                                                  11.3 The Factorial Design: Two-Way Analysis of Variance 438
10.1 Comparing the Means of Two Independent
                                                                         Testing for Factor and Interaction Effects 439
     Populations 366
                                                                         Multiple Comparisons: The Tukey Procedure 444
      Pooled-Variance t Test for the Difference Between Two
      Means 366                                                          Visualizing Interaction Effects: The Cell Means Plot 445
      Confidence Interval Estimate for the Difference Between            Interpreting Interaction Effects 446
      Two Means 371                                               USING STATISTICS @ Perfect Parachutes Revisited 451
      t Test for the Difference Between Two Means Assuming              SUMMARY 451
      Unequal Variances 372
                                                                        KEY EQUATIONS 451
THINK ABOUT THIS: “This Call May Be Monitored ... ” 374
                                                                        KEY TERMS 453
10.2 Comparing the Means of Two Related Populations 377
                                                                        CHAPTER REVIEW PROBLEMS 453
        Paired t Test 378
                                                                        MANAGING ASHLAND MULTICOMM SERVICES 457
        Confidence Interval Estimate for the Mean
        Difference 383                                                  DIGITAL CASE 458

10.3 Comparing the Proportions of Two Independent                       REFERENCES 458
     Populations 385                                                    CHAPTER 11 EXCEL GUIDE 459
        Z Test for the Difference Between Two Proportions 386             EG11.1 The Completely Randomized Design: One-Way
        Confidence Interval Estimate for the Difference Between           Analysis of Variance 459
        Two Proportions 390                                               EG11.2 The Randomized Block Design 461
10.4 F Test for the Ratio of Two Variances 392                            EG11.3 The Factorial Design: Two-Way Analysis of
                                                                          Variance 462
USING STATISTICS @ BLK Beverages Revisited 397
                                                                        CHAPTER 11 MINITAB GUIDE 464
     SUMMARY 398                                                          MG11.1 The Completely Randomized Design: One-Way
     KEY EQUATIONS 399                                                    Analysis of Variance 464
     KEY TERMS 400                                                        MG11.2 The Randomized Block Design 465
     CHAPTER REVIEW PROBLEMS 400                                          MG11.3 The Factorial Design: Two-Way Analysis of
     MANAGING ASHLAND MULTICOMM SERVICES 404
                                                                          Variance 465
     DIGITAL CASE 405
     REFERENCES 405
     CHAPTER 10 EXCEL GUIDE 406
                                                                  12 Chi-Square Tests and
        EG10.1 Comparing the Means of Two Independent                    Nonparametric Tests                                 466
        Populations 406
        EG10.2 Comparing the Means of Two Related                 USING STATISTICS @ T.C. Resort Properties 467
        Populations 408                                           12.1 Chi-Square Test for the Difference Between Two
        EG10.3 Comparing the Proportions of Two Independent            Proportions 468
        Populations 409                                           12.2 Chi-Square Test for Differences Among More Than Two
        EG10.4 F Test for the Ratio of Two Variances 410               Proportions 475
     CHAPTER 10 MINITAB GUIDE 411                                         The Marascuilo Procedure 478
        MG10.1 Comparing the Means of Two Independent                         Online Topic: The Analysis of Proportions (ANOP) 480
        Populations 411
                                                                  12.3 Chi-Square Test of Independence 481
        MG10.2 Comparing the Means of Two Related
        Populations 411                                           12.4 McNemar Test for the Difference Between Two Proportions
        MG10.3 Comparing the Proportions of Two Independent            (Related Samples) 487
        Populations 412                                           12.5 Chi-Square Test for the Variance or Standard
        MG10.4 F Test for the Ratio of Two Variances 412               Deviation 490
                                                                  12.6 Wilcoxon Rank Sum Test: Nonparametric Analysis
                                                                       for Two Independent Populations 494
11 Analysis of Variance                                    414    12.7 Kruskal-Wallis Rank Test: Nonparametric Analysis
                                                                       for the One-Way ANOVA 500
USING STATISTICS @ Perfect Parachutes 415
                                                                  12.8      Online Topic: Wilcoxon Signed Ranks test:
11.1 The Completely Randomized Design: One-Way Analysis                Nonparametric Analysis for Two Related Populations 505
     of Variance 416                                              12.9      Online Topic: Friedman Rank Test: Nonparametric
        One-Way ANOVA F Test for Differences Among More Than           Analysis for the Randomized Block Design 506
        Two Means 416
        Multiple Comparisons: The Tukey-Kramer Procedure 422      USING STATISTICS @ T.C. Resort Properties Revisited 506
            Online Topic: The Analysis of Means (ANOM) 424              SUMMARY 506
        ANOVA Assumptions 424                                           KEY EQUATIONS 507
        Levene Test for Homogeneity of Variance 425                     KEY TERMS 508
xviii     CONTENTS

        CHAPTER REVIEW PROBLEMS 508                                         Confidence Interval Estimate for the Slope 550
        MANAGING ASHLAND MULTICOMM SERVICES 511                             t Test for the Correlation Coefficient 551
        DIGITAL CASE 512                                            13.8 Estimation of Mean Values and Prediction of Individual
        REFERENCES 513                                                   Values 554
        CHAPTER 12 EXCEL GUIDE 514                                         The Confidence Interval Estimate 554
          EG12.1 Chi-Square Test for the Difference Between                The Prediction Interval 556
          Two Proportions 514                                       13.9 Pitfalls in Regression 558
          EG12.2 Chi-Square Test for Differences Among More Than    THINK ABOUT THIS: By Any Other Name 561
          Two Proportions 514
                                                                    USING STATISTICS @ Sunflowers Apparel
          EG12.3 Chi-Square Test of Independence 515                     Revisited 561
          EG12.4 McNemar Test for the Difference Between Two             SUMMARY 562
          Proportions (Related Samples) 515
                                                                         KEY EQUATIONS 563
          EG12.5 Chi-Square Test for the Variance or Standard
          Deviation 516                                                  KEY TERMS 564
          EG12.6 Wilcoxon Rank Sum Test: Nonparametric Analysis          CHAPTER REVIEW PROBLEMS 564
          for Two Independent Populations 516                            MANAGING ASHLAND MULTICOMM SERVICES 569
          EG12.7 Kruskal-Wallis Rank Test: Nonparametric Analysis        DIGITAL CASE 569
          for the One-Way ANOVA 517                                      REFERENCES 570
        CHAPTER 12 MINITAB GUIDE 518                                     CHAPTER 13 EXCEL GUIDE 571
          MG12.1 Chi-Square Test for the Difference Between Two             EG13.1 Types of Regression Models 571
          Proportions 518                                                   EG13.2 Determining the Simple Linear Regression
          MG12.2 Chi-Square Test for Differences Among More                 Equation 571
          Than Two Proportions 518                                          EG13.3 Measures of Variation 572
          MG12.3 Chi-Square Test of Independence 518                        EG13.4 Assumptions 572
          MG12.4 McNemar Test for the Difference Between Two                EG13.5 Residual Analysis 572
          Proportions (Related Samples) 518                                 EG13.6 Measuring Autocorrelation: The Durbin-Watson
          MG12.5 Chi-Square Test for the Variance or Standard               Statistic 572
          Deviation 518                                                     EG13.7 Inferences About the Slope and Correlation
          MG12.6 Wilcoxon Rank Sum Test: Nonparametric                      Coefficient 573
          Analysis for Two Independent Populations 519                      EG13.8 Estimation of Mean Values and Prediction
          EG12.7 Kruskal-Wallis Rank Test: Nonparametric Analysis           of Individual Values 573
          for the One-Way ANOVA 519                                      CHAPTER 13 MINITAB GUIDE 574
                                                                            MG13.1 Types of Regression Models 574
                                                                            MG13.2 Determining the Simple Linear Regression
13 Simple Linear                                                            Equation 574
                                                                            MG13.3 Measures of Variation 574
         Regression                                           520           MG13.4 Assumptions 574
                                                                            MG13.5 Residual Analysis 574
USING STATISTICS @ Sunflowers Apparel 521
                                                                            MG13.6 Measuring Autocorrelation: The Durbin-Watson
13.1 Types of Regression Models 522                                         Statistic 575
13.2 Determining the Simple Linear Regression Equation 524                  MG13.7 Inferences About the Slope and Correlation
       The Least-Squares Method 525                                         Coefficient 575
       Predictions in Regression Analysis: Interpolation Versus             MG13.8 Estimation of Mean Values and Prediction
       Extrapolation 527                                                    of Individual Values 575
       Computing the Y Intercept, b0 and the Slope, b1 528
VISUAL EXPLORATIONS: Exploring Simple Linear Regression
     Coefficients 530                                               14 Introduction to Multiple
13.3 Measures of Variation 533
          Computing the Sum of Squares 533
                                                                           Regression                                           576
          The Coefficient of Determination 534                      USING STATISTICS @ OmniFoods 577
          Standard Error of the Estimate 536
                                                                    14.1 Developing a Multiple Regression Model 578
13.4 Assumptions 538                                                       Visualizing Multiple Regression Data 578
13.5 Residual Analysis 539                                                 Interpreting the Regression Coefficients 578
       Evaluating the Assumptions 539                                      Predicting the Dependent Variable Y 581
13.6 Measuring Autocorrelation: The Durbin-Watson                   14.2 r2, Adjusted r2, and the Overall F Test 584
     Statistic 543                                                          Coefficient of Multiple Determination 584
          Residual Plots to Detect Autocorrelation 543                      Adjusted r2 585
          The Durbin-Watson Statistic 544                                   Test for the Significance of the Overall Multiple
13.7 Inferences About the Slope and Correlation Coefficient 547             Regression Model 585
       t Test for the Slope 548                                     14.3 Residual Analysis for the Multiple Regression
       F Test for the Slope 549                                          Model 588
                                                                                                                CONTENTS          xix

14.4 Inferences Concerning the Population Regression              15.3 Collinearity 642
     Coefficients 590                                             15.4 Model Building 644
       Tests of Hypothesis 590                                             The Stepwise Regression Approach to Model Building 646
       Confidence Interval Estimation 591                                  The Best-Subsets Approach to Model Building 647
14.5 Testing Portions of the Multiple Regression                           Model Validation 652
     Model 593                                                    15.5 Pitfalls in Multiple Regression and Ethical Issues 653
       Coefficients of Partial Determination 597                         Pitfalls in Multiple Regression 653
14.6 Using Dummy Variables and Interaction Terms in                      Ethical Issues 654
     Regression Models 599                                        15.6 (     Online Topic) Influence Analysis 654
       Dummy variables 599
       Interactions 602                                           15.7 (     Online Topic) Analytics and Data Mining 654
14.7 Logistic Regression 609                                      USING STATISTICS @ WHIT-DT Revisited 654
                                                                         SUMMARY 655
USING STATISTICS @ OmniFoods Revisited 614
                                                                         KEY EQUATIONS 656
     SUMMARY 614
                                                                         KEY TERMS 656
     KEY EQUATIONS 616
                                                                         CHAPTER REVIEW PROBLEMS 656
     KEY TERMS 617
                                                                         THE MOUNTAIN STATES POTATO COMPANY 658
     CHAPTER REVIEW PROBLEMS 617
                                                                         DIGITAL CASE 659
     MANAGING ASHLAND MULTICOMM SERVICES 620
                                                                         REFERENCES 659
     DIGITAL CASE 620
                                                                         CHAPTER 15 EXCEL GUIDE 660
     REFERENCES 621
                                                                           EG15.1 The Quadratic Regression Model 660
     CHAPTER 14 EXCEL GUIDE 622
                                                                           EG15.2 Using Transformations in Regression Models 660
       EG14.1 Developing a Multiple Regression Model 622
                                                                           EG15.3 Collinearity 660
       EG14.2 r2, Adjusted r2, and the Overall F Test 623
                                                                           EG15.4 Model Building 660
       EG14.3 Residual Analysis for the Multiple Regression
       Model 623                                                         CHAPTER 15 MINITAB GUIDE 661
       EG14.4 Inferences Concerning the Population Regression              MG15.1 The Quadratic Regression Model 661
       Coefficients 624                                                    MG15.2 Using Transformations in Regression Models 662
       EG14.5 Testing Portions of the Multiple Regression                  MG15.3 Collinearity 662
       Model 624                                                           MG15.4 Model Building 662
       EG14.6 Using Dummy Variables and Interaction Terms
       in Regression Models 624
       EG14.7 Logistic Regression 624
     CHAPTER 14 MINITAB GUIDE 625
       MG14.1 Developing a Multiple Regression Model 625
                                                                  16 Time-Series Forecasting 664
       MG14.2 r2, Adjusted r2, and the Overall F Test 626         USING STATISTICS @ The Principled 665
       MG14.3 Residual Analysis for the Multiple Regression       16.1 The Importance of Business Forecasting 666
       Model 626
                                                                  16.2 Component Factors of Time-Series Models 666
       MG14.4 Inferences Concerning the Population Regression
       Coefficients 626                                           16.3 Smoothing an Annual Time Series 667
       MG14.5 Testing Portions of the Multiple Regression                  Moving Averages 668
       Model 626                                                           Exponential Smoothing 670
       MG14.6 Using Dummy Variables and Interaction Terms         16.4 Least-Squares Trend Fitting and Forecasting 673
       in Regression Models 626                                          The Linear Trend Model 673
       MG14.7 Logistic Regression 627                                    The Quadratic Trend Model 675
                                                                         The Exponential Trend Model 676
                                                                           Model Selection Using First, Second, and Percentage
15 Multiple Regression Model                                               Differences 678
                                                                  16.5 Autoregressive Modeling for Trend Fitting and
       Building                                           628          Forecasting 684
                                                                  16.6 Choosing an Appropriate Forecasting Model 692
USING STATISTICS @ WHIT-DT 629                                           Performing a Residual Analysis 693
15.1 The Quadratic Regression Model 630                                    Measuring the Magnitude of the Residuals Through Squared
       Finding the Regression Coefficients and Predicting Y 630            or Absolute Differences 693
       Testing for the Significance of the Quadratic Model 633             Using the Principle of Parsimony 694
       Testing the Quadratic Effect 633                                    A Comparison of Four Forecasting Methods 694
       The Coefficient of Multiple Determination 635              16.7 Time-Series Forecasting of Seasonal Data 696
15.2 Using Transformations in Regression Models 638                        Least-Squares Forecasting with Monthly or Quarterly Data 697
      The Square-Root Transformation 638                          16.8       Online Topic: Index Numbers 703
      The Log Transformation 639                                  THINK ABOUT THIS: Let the Model User Beware 703
xx      CONTENTS

USING STATISTICS @ The Principled Revisited 703                        MANAGING ASHLAND MULTICOMM SERVICES 753
     SUMMARY 704                                                       REFERENCES 754
     KEY EQUATIONS 704                                                 CHAPTER 17 EXCEL GUIDE 755
     KEY TERMS 705                                                       EG17.1 The Theory of Control Charts 755
     CHAPTER REVIEW PROBLEMS 706                                         EG17.2 Control Chart for the Proportion: The p Chart 755
     MANAGING ASHLAND MULTICOMM SERVICES 707                             EG17.3 The Red Bead Experiment: Understanding Process
                                                                         Variability 756
     DIGITAL CASE 708
                                                                         EG17.4 Control Chart for an Area of Opportunity: The c
     REFERENCES 708                                                      Chart 756
     CHAPTER 16 EXCEL GUIDE 709                                          EG17.5 Control Charts for the Range and the Mean 757
       EG16.1 The Importance of Business Forecasting 709                 EG17.6 Process Capability 758
       EG16.2 Component Factors of Time-Series Models 709                EG17.7 Total Quality Management 759
       EG16.3 Smoothing an Annual Time Series 709                        EG17.8 Six Sigma 759
       EG16.4 Least-Squares Trend Fitting and Forecasting 710          CHAPTER 17 MINITAB GUIDE 759
       EG16.5 Autoregressive Modeling for Trend Fitting and              MG17.1 The Theory of Control Charts 759
       Forecasting 711                                                   MG17.2 Control Chart for the Proportion:
       EG16.6 Choosing an Appropriate Forecasting Model 711              The p Chart 759
       EG16.7 Time-Series Forecasting of Seasonal Data 712               MG17.3 The Red Bead Experiment: Understanding
     CHAPTER 16 MINITAB GUIDE 713                                        Process Variability 759
       MG16.1 The Importance of Business Forecasting 713                 MG17.4 Control Chart for an Area of Opportunity: The c
       MG16.2 Component Factors of Time-Series Models 713                Chart 756
       MG16.3 Smoothing an Annual Time Series 713                        MG17.5 Control Charts for the Range and the Mean 760
       MG16.4 Least-Squares Trend Fitting and Forecasting 713            MG17.6 Process Capability 761
       MG16.5 Autoregressive Modeling for Trend Fitting and              MG17.7 Total Quality Management 761
       Forecasting 714                                                   MG17.8 Six Sigma 761
       MG16.6 Choosing an Appropriate Forecasting Model 714
       MG16.7 Time-Series Forecasting of Seasonal Data 714

                                                                  18 A Roadmap for Analyzing
17 Statistical Applications in                                          Data                                                 762
       Quality Management                                   716   USING STATISTICS @ YourBusiness 763
USING STATISTICS @ Beachcomber Hotel 717                          18.1 Analyzing Numerical Variables 765
                                                                         How to Describe the Characteristics of a Numerical
17.1 The Theory of Control Charts 718                                    Variable 766
17.2 Control Chart for the Proportion: The p Chart 720                   How to Draw Conclusions About the Population Mean
17.3 The Red Bead Experiment: Understanding Process                      or Standard Deviation 766
     Variability 726                                                     How to Determine Whether the Mean or Standard Deviation
                                                                         Differs Depending on the Group 766
17.4 Control Chart for an Area of Opportunity: The c
     Chart 728                                                           How to Determine Which Factors Affect the Value of
                                                                         a Variable 767
17.5 Control Charts for the Range and the Mean 732                       How to Predict the Value of a Variable Based on the Value
       The R Chart 732                                                   of Other Variables 767
       The X Chart 734                                                   How to Determine Whether the Values of a Variable Are
17.6 Process Capability 737                                              Stable over Time 767
       Customer Satisfaction and Specification Limits 737         18.2 Analyzing Categorical Variables 767
       Capability Indices 739                                            How to Describe the Proportion of Items of Interest in Each
       CPL, CPU, and Cpk 740                                             Category 768
17.7 Total Quality Management 742                                        How to Reach Conclusions About the Proportion of Items
                                                                         of Interest 768
17.8 Six Sigma 744                                                       How to Determine Whether the Proportion of Items
       The DMAIC Model 744                                               of Interest Differs Depending on the Group 768
       Roles in a Six Sigma Organization 745                             How to Predict the Proportion of Items of Interest Based
USING STATISTICS @ Beachcomber Hotel Revisited 746                       on the Value of Other Variables 768
     SUMMARY 747                                                         How to Determine Whether the Proportion of Items
                                                                         of Interest Is Stable over Time 769
     KEY EQUATIONS 747
     KEY TERMS 748                                                USING STATISTICS @ YourBusiness Revisited 769
     CHAPTER REVIEW PROBLEMS 748                                       DIGITAL CASE 769

     THE HARNSWELL SEWING MACHINE COMPANY CASE 751                     CHAPTER REVIEW PROBLEMS 769
                                                                                                  CONTENTS       xxi

  Online Chapter:                                             D.3 Configuring Excel for PHStat2 Usage 793
                                                              D.4 Using the Visual Explorations Add-in
19 Decision Making                                                  Workbook 795
                                                              D.5 Checking for the Presence of the Analysis
USING STATISTICS @ Reliable Fund                                    ToolPak 795
19.1 Payoff Tables and Decision Trees                      E. Tables 796
19.2 Criteria for Decision Making                             E.1 Table of Random Numbers 796
       Maximax Payoff                                         E.2 The Cumulative Standardized Normal
       Maximin Payoff                                               Distribution 798
       Expected Monetary Value
                                                              E.3 Critical Values of t 800
       Expected Opportunity Loss
       Return-to-Risk Ratio
                                                              E.4 Critical Values of x2 802
19.3 Decision Making with Sample Information                  E.5 Critical values of F 803
19.4 Utility                                                  E.6 Lower and Upper Critical Values, T1, of Wilcoxon
                                                                    Rank Sum Test 807
THINK ABOUT THIS: Risky Business
                                                              E.7 Critical Values of the Studentized Range, Q 808
USING STATISTICS @ Reliable Fund Revisited
                                                              E.8 Critical Values dL and du of the Durbin-Watson
     CHAPTER 19 EXCEL GUIDE
                                                                    Statistic, D 810
       EG19.1 Payoff Tables and Decision Trees
       EG19.2 Criteria for Decision Making                    E.9 Control Chart Factors 811
                                                              E.10 The Standardized Normal Distribution 812
Appendices 773                                             F. Additional Excel Procedures 813
A. Basic Math Concepts and Symbols 774                        F.1 Enhancing Workbook Presentation 813
   A.1 Rules for Arithmetic Operations 774                    F.2 Useful Keyboard Shortcuts 814
   A.2 Rules for Algebra: Exponents and Square Roots 774      F.3 Verifying Formulas and Worksheets 815
   A.3 Rules for Logarithms 775                               F.4 Chart Formatting 815
   A.4 Summation Notation 776                                 F.5 Creating Histograms for Discrete Probability
                                                                    Distributions 816
   A.5 Statistical Symbols 779
                                                              F.6 Pasting with Paste Special 816
   A.6 Greek Alphabet 779
                                                           G. PHStat2, Excel, and Minitab FAQs 818
B. Basic Computing Skills 780
                                                              G.1 PHStat2 FAQs 818
   B.1 Objects in a Window 780
                                                              G.2 Excel FAQs 818
   B.2 Basic Mouse Operations 781
                                                              G.3 FAQs for Minitab 819
   B.3 Dialog Box Interactions 781
   B.4 Unique Features 783
C. Companion Website Resources 784
   C.1 Visiting the Companion Website for This Book 784    Self-Test Solutions and Answers to Selected
   C.2 Downloading the Files for This Book 784             Even-Numbered Problems 820
   C.3 Accessing the Online Topics Files 784
   C.4 Details of Downloadable Files 784                   Index 850
D. Software Configuration Details 792
   D.1 Checking for and Applying Excel Updates 792
   D.2 Concise Instructions for Installing PHStat2 792
Preface
Educational Philosophy
              Seeking ways to continuously improve the teaching of business statistics is the core value that
              guides our works. We actively participate in Decision Sciences Institute (DSI), American Statistical
              Association (ASA), and Making Statistics More Effective in Schools and Business (MSMESB)
              conferences. We use the Guidelines for Assessment and Instruction (GAISE) reports as well as our
              reflections on teaching business statistics to a diverse student body at several large universities.
              These experiences have helped us identify the following key principles:

                 1. Show students the relevance of statistics Students need a frame of reference when learning
                    statistics, especially when statistics is not their major. That frame of reference for business
                    students should be the functional areas of business, such as accounting, finance, information
                    systems, management, and marketing. Each statistics topic needs to be presented in an
                    applied context related to at least one of these functional areas. The focus in teaching each
                    topic should be on its application in business, the interpretation of results, the evaluation of
                    the assumptions, and the discussion of what should be done if the assumptions are violated.
                 2. Familiarize students with the statistical applications used in the business world
                    Integrating these programs into all aspects of an introductory statistics course allows the
                    course to focus on interpretation of results instead of computations. Introductory business
                    statistics courses should recognize that programs with statistical functions are commonly
                    found on a business decision maker’s desktop computer, therefore making the interpretation
                    of results more important than the tedious hand calculations required to produce them.
                 3. Provide clear instructions to students for using statistical applications Books should
                    explain clearly how to use programs such as Excel and Minitab with the study of statistics,
                    without having those instructions dominate the book or distract from the learning of statisti-
                    cal concepts.
                 4. Give students ample practice in understanding how to apply statistics to business Both
                    classroom examples and homework exercises should involve actual or realistic data as much as
                    possible. Students should work with data sets, both small and large, and be encouraged to look
                    beyond the statistical analysis of data to the interpretation of results in a managerial context.

              New to This Edition: MyStatLab
              Custom MyStatLab course materials designed for specific use with this book are available.
              MyStatLab is Pearson Education’s online learning, homework, and assessment tool that provides a
              rich and flexible set of course materials, including free-response exercises that are algorithmically
              generated for unlimited practice and mastery. MyStatLab provides students with a personalized,
              interactive learning environment that helps them to independently improve their understanding and
              performance in a course. MyStatLab allows instructors to deliver portions of a course online, to per-
              form course management functions, and to create a supportive online community. In addition,
              instructors can use the MyStatLab homework and test manager to select and assign their own online
              exercises as well as import TestGen tests.
                   The MyStatLab for Basic Business Statistics features several improvements over earlier versions
              including a more intuitive user design that presents a simpler interface with fewer pop-up windows.
              This MyStatLab also provides mobile device access through free apps that can be downloaded for
              iPhones, iPads, and Andriod phones. (iPad users can even download a free app to access all of their
              Pearson eTexts, seeing their instructors annotations and gaining links to Do Homework, Take a Test,
              and Study Plan functions.)




                                                                                                               xxiii
xxiv   PREFACE


                 New to This Edition: Enhanced Statistical Coverage
                 This 12th edition of Basic Business Statistics builds on previous editions with these new and
                 enhanced features:
                     • New chapter-ending “Using Statistics ... Revisited” sections that reinforce the statistical
                       methods and applications discussed in each chapter.
                     • The use of the DCOVA (Define, Collect, Organize, Visualize, and Analyze) framework as an
                       integrated approach for applying statistics to help solve business problems.
                     • Many new applied examples and exercises, with data from The Wall Street Journal, USA
                       Today, and other sources.
                     • “Managing Ashland MultiComm Services,” a new integrated case that appears at the ends of
                       chapters throughout the book (replacing the Springville Herald case).
                     • “Digital Cases,” interactive PDF files that create a new series of cases that appear at the
                       ends of chapters throughout the book (replacing the Web Cases).
                     • An expanded discussion of using Excel and Minitab to summarize and explore multidimen-
                       sional data.
                     • Revised and updated “Think About This” essays (formerly entitled “From the Author’s
                       Desktop”) that provide greater insight into what has just been learned and raise important
                       issues about the application of statistical knowledge.
                     • Additional in-chapter Excel and Minitab results.
                     • A new online section that discusses analytics and data mining.

                 New to This Edition: Expanded Excel and Minitab Guides
                 In this 12th edition of Basic Business Statistics, the instructions for using Excel and Minitab have
                 been revised, reorganized, and enhanced in new end-of-chapter guides and back-of-the book appen-
                 dices. These sections support students by:
                     • Providing a readiness checklist and orientation that guide students through the process of get-
                       ting ready to use Excel or Minitab (see Chapter 1 and the Chapter 1 Excel and Minitab Guides).
                     • Incorporating Excel Guide workbooks that serve as models and templates for using Excel for
                       statistical problem solving. These free and reusable workbooks, annotated examples of which
                       appear throughout the chapters of this book, can be used by students in their other courses or
                       in their jobs.
                     • Allowing students to use Excel with or without PHStat2 and with or without the Analysis
                       ToolPak (an Excel component that is not available in Mac Excel 2008).
                     • Expanding the scope of Minitab Guide instructions.
                     • Reviewing common operations, such as opening, saving, and printing results (see Chapter 1
                       Excel and Minitab Guides).
                     • Explaining the different types of files available online that support this book and how to
                       download those free files from this book’s companion website (Appendix C).
                     • Providing a separate appendix that discusses software configuration issues, including how to
                       check for Excel and Minitab updates and how to configure Excel for use with PHStat2 or the
                       Analysis ToolPak (Appendix D).
                     • An appendix that discusses formatting and other intermediate-level Excel operations
                       (Appendix F).
                     • Answering frequently asked questions about Excel, PHStat2, the Pearson statistical add-in
                       for Microsoft Windows–based Excel versions, and Minitab (the new Appendix G).
                     • In Appendix Section C.4, offering a complete list of all downloadable files and programs for
                       this book. (See “Student Resources” on page xxvi for more details about the files and programs
                       that can be downloaded.)


Chapter-by-Chapter Changes in the 12th Edition
                 Chapters begin with a redesigned opening page that displays the chapter sections and subsections
                 and conclude with the new Excel and Minitab Guides that discuss how to apply Excel and Minitab
                 to the statistical methods discussed in a chapter. Minitab Guides have been expanded to better match
                 the scope of the Excel Guides. End-of-chapter Digital Cases that use interactive documents, in lieu
                                                                                 PREFACE       xxv

of simulated web pages, update the former Web Cases. There is a new integrated case, “Managing
Ashland MultiComm Services,” that replaces the “Managing the Springville Herald” case (see
Chapters 2, 3, 5 through 7, 9 through 14, 16, and 17). Appendices B through D and F and G have
been revised, reorganized, and updated.
     Highlights of changes to individual chapters follow.
    Chapter 1 The 11th edition’s Section 1.4 has been moved to Chapter 2. Section 1.6 has been
     rewritten and retitled “How to Use This Book” and now includes the “Checklist for Getting
     Started” (with Excel or Minitab). There are new undergraduate and graduate surveys.
    Chapter 2 This chapter has been completely reorganized. Sections 1.4 of the previous edition,
     concerning data collection, has been moved to this chapter. The Define, Collect, Organize,
     Visualize, and Analyze approach to solving business problems has been incorporated. The
     material on tables and charts has been reorganized so that the sections on organizing data into
     tables is presented first, in Sections 2.2 and 2.3, followed by sections on visualizing data in
     graphs in Sections 2.4–2.7. There is a new section on organizing multidimensional data
     (Section 2.7). There are new Excel and Minitab Guide sections that discuss multidimensional
     data. The Minitab Guide that replaces the Minitab Appendix has been greatly expanded. In
     addition, there are new examples throughout the chapter, and a new data set on bond funds has
     been created.
    Chapter 3 A new data set on bond funds has been created. The section “Numerical Measures
     for a Population” has been moved after the section on quartiles and boxplots. “Numerical
     Descriptive Measures from a Population” has been deleted.
    Chapter 4 The chapter example has been updated. There are new problems throughout the
     chapter. The “Think About This” essay about Bayes’ theorem has been condensed and
     updated. In combinations and permutations, x is used instead of X to be consistent with bino-
     mial notation in Chapter 5.
    Chapter 5 This chapter has revised notation for the binomial, Poisson, and hypergeometric
     distributions. It uses lower-case x and includes the parameter after an | sign in the equa-
     tion. To reduce the size of the book, the tables of the binomial and Poisson distributions
     (Tables E.6 and E.7) have been placed online. There are new problems throughout the
     chapter.
    Chapter 6 This chapter has an updated Using Statistics scenario. The “Think About This”
     essay on the importance of the normal distribution has been revised. The discussion of the
     exponential distribution has been revised.
    Chapter 7 A new “Think About This” essay replaces and expands on the pros and cons of web-
     based surveys, using a famous historical example. “Sampling from Finite Populations” is
     now an online topic.
    Chapter 8 This chapter includes problems on sigma known in Section 8.1.
    Chapter 9 This chapter includes problems on sigma known in Section 9.1. “Power of a Test” is
     now an online topic.
    Chapter 10 This chapter has a new example on the paired t-test on textbook prices.
    Chapter 11 This chapter has an “Online Topic” subsection titled “The Analysis of Means
     (ANOM).”
    Chapter 12 This chapter has an “Online Topic” subsection titled “The Analysis of Proportions
     (ANOP).” The Wilcoxon signed ranks test and the Friedman test are now online topicss.
    Chapter 13 The “Think About This” essay has been revised. There are new problems through-
     out the chapter.
    Chapter 14 This chapter has various new problems.
    Chapter 15 This chapter has a new “Online Topic” section titled “Analytics and Data Mining.”
     There are new problems throughout the chapter.
    Chapter 16 This chapter has updated examples throughout the chapter. “Index Numbers” is
     now an online topic.
    Chapter 17 This chapter has been edited for conciseness without any loss of concepts or clarity.
    Chapter 18 This chapter now includes an interactive roadmap for analyzing data as part of a
     new Digital Case. There are many new problems in the chapter.
    Chapter 19 This chapter (formerly Chapter 17) has become an online chapter and is available
     for download through this book’s companion website.
xxvi   PREFACE


Hallmark Features
                 We have continued many of the traditions of past editions and have highlighted some of these
                 features below.
                     Using Statistics Business Scenarios—Each chapter begins with a Using Statistics example that
                       shows how statistics is used in the functional areas of business—accounting, finance, infor-
                       mation systems, management, and marketing. Each scenario is used throughout the chapter
                       to provide an applied context for the concepts.
                     Emphasis on Data Analysis and Interpretation of Software Results—We believe that
                       the use of computer software is an integral part of learning statistics. Our focus empha-
                       sizes analyzing data by interpreting results while reducing emphasis on doing compu-
                       tations. For example, in the coverage of tables and charts in Chapter 2, the focus is on
                       the interpretation of various charts and on when to use each chart. In our coverage of
                       hypothesis testing in Chapters 9 through 12, and regression and time series forecasting in
                       Chapters 13–16, extensive computer results have been included so that the p-value
                       approach can be emphasized.
                     Pedagogical Aids—An active writing style is used, with boxed numbered equations, set-off
                       examples to provide reinforcement for learning concepts, problems divided into “Learning
                       the Basics” and “Applying the Concepts,” key equations, and key terms.
                     Answers—Many answers to the even-numbered exercises are included at the end of the book.
                     Flexibility Using Excel—For almost every statistical method discussed, this book presents
                       more than one way of using Excel. Students can use In-Depth Excel instructions to directly
                       work with the worksheet cell-level details or they can use the PHStat2 instructions or use the
                       Analysis ToolPak instructions to automate the creation of those same details.
                     Digital Cases—An end-of-chapter Digital Case is included for each of the first 16 chapters.
                       Most Digital Cases extend a Using Statistics business scenario by posing additional ques-
                       tions and raising issues about the scenario. Students examine interactive documents to sift
                       through claims and assorted information in order to discover the data most relevant to a sce-
                       nario. Students then determine whether the conclusions and claims are supported by the data.
                       In doing so, students discover and learn how to identify common misuses of statistical infor-
                       mation. (Instructional tips for using the Digital Cases and solutions to the Digital Cases are
                       included in the Instructor’s Solutions Manual.)
                     Case Studies and Team Projects—Detailed case studies are included in numerous chapters. A
                      “Managing Ashland MultiComm Services” continuing case, a team project related to bond
                      funds, and undergraduate and graduate student surveys are included at the end of most chap-
                      ters, and these serve to integrate learning across the chapters.
                     Visual Explorations—The Excel add-in workbook allows students to interactively explore
                       important statistical concepts in descriptive statistics, the normal distribution, sampling dis-
                       tributions, and regression analysis. For example, in descriptive statistics, students observe the
                       effect of changes in the data on the mean, median, quartiles, and standard deviation. With the
                       normal distribution, students see the effect of changes in the mean and standard deviation on
                       the areas under the normal curve. In sampling distributions, students use simulation to
                       explore the effect of sample size on a sampling distribution. In regression analysis, students
                       have the opportunity to fit a line and observe how changes in the slope and intercept affect
                       the goodness of fit.


Student Resources
                     Student Solutions Manual—Created by Professor Pin Tian Ng of Northern Arizona University,
                       this manual provides detailed solutions to virtually all the even-numbered exercises and
                       worked-out solutions to the self-test problems.
                     Companion website—This book comes with a companion website from which the following
                      resources can be downloaded for free (see Appendix C that starts on page 784 for more
                      details about these resources, including how to visit the companion website):
                                                                                                  PREFACE      xxvii

                   • Data files Excel and Minitab data files used by in-chapter examples and problems (in .xls
                     and .mtw formats).
                   • Online Chapter The electronic-only Chapter 19: Decision Making in PDF format.
                   • Online Topics Online topics are PDF files that discuss additional topics for Chapters 5, 6, 7,
                     8, 9, 11, 12, 15, and 16.
                   • Excel Guide workbooks Self-documenting Excel Guide workbooks illustrate solutions for
                     more than 60 statistical topics that serve as freely reusable templates for future problem solv-
                     ing.
                   • Case files Supporting files are provided for the Digital Cases and the Managing Ashland
                     MultiComm Services Case.
                   • Visual Explorations The files needed to use the Visual Explorations Excel add-in work-
                     book.
                   • Using Excel 2003 Guide This guide presents, where necessary, alternate Excel Guide
                     instructions for users of this older version of Excel.
                   • PHStat2 The latest version of PHStat2, the Pearson statistical add-in for Windows-based
                     Excel, version 2003 and later. This version eliminates the use of the Excel Analysis ToolPak
                     add-ins, thereby simplifying installation and setup.

                   MyStatLab—MyStatLab provides students with direct access to the companion website
                    resources as well as the following exclusive online features and tools:
                   • Interactive tutorial exercises A comprehensive set of exercises have been written espe-
                     cially for use with this book that are algorithmically generated for unlimited practice and
                     mastery. Most exercises are free-response exercises and provide guided solutions, sample
                     problems, and learning aids for extra help at point of use.
                   • Personalized study plan A plan indicates which topics have been mastered and creates
                     direct links to tutorial exercises for topics that have not been mastered. MyStatLab manages
                     the study plan, updating its content based on the results of future online assessments.
                   • Pearson Tutor Center (www.pearsontutorservices.com) The MyStatlab student access
                     code grants access to this online resource, staffed by qualified instructors who provide book-
                     specific tutoring via phone, fax, e-mail, and interactive web sessions.
                   • Integration with Pearson eTexts iPad users can download a free app at www.apple.com/
                     ipad/apps-for-ipad/ and then sign in using their MyStatLab account to access a bookshelf of
                     all their Pearson eTexts. The iPad app also allows access to the Do Homework, Take a Test,
                     and Study Plan pages of their MyStatLab course.
                   • Mobile Dashboard Allows students to use their mobile devices to log in and review informa-
                     tion from the dashboard of their courses: announcements, assignments, results, and progress
                     bars for completed work. This app is available for iPhones, iPads, and Android phones, and is
                     designed to promote effective study habits rather than to allow students to complete assign-
                     ments on their mobile devices.
               @RISK trial Palisade Corporation, the maker of the market-leading risk and decision analysis
               Excel add-ins, @RISK and the DecisionTools® Suite, provides special academic versions of its
               software to students (and faculty). Its flagship product, @RISK, debuted in 1987 and performs risk
               analysis using Monte Carlo simulation.
                   @RISK and the DecisionTools Suite are used widely in undergraduate and graduate business
               programs worldwide. Thanks to the company’s generous academic sales program, more than 40,000
               students learn to make better decisions using @RISK and the DecisionTools Suite each year.
                   To download a trial version of @RISK software, visit www.palisadecom/academic/.


Instructor Resources
               Instructor’s Resource Center—Reached through a link at www.pearsonhighered.com/levine,
               the Instructor’s Resource Center contains the electronic files for the complete Instructor’s Solutions
               Manual, the Test Item File, and PowerPoint lecture presentations.
                   • Register, redeem, log in At www.pearsonhighered.com/irc, instructors can access a vari-
                     ety of print, media, and presentation resources that are available with this book in downloadable
xxviii   PREFACE

                         digital format. Resources are also available for course management platforms such as
                         Blackboard, WebCT, and CourseCompass.
                       • Need help? Pearson Education’s dedicated technical support team is ready to assist instruc-
                         tors with questions about the media supplements that accompany this text. Visit http://
                         247.prenhall.com for answers to frequently asked questions and toll-free user support
                         phone numbers. The supplements are available to adopting instructors. Detailed descriptions
                         are provided at the Instructor’s Resource Center.
                   Instructor’s Solutions Manual—Created by Professor Pin Tian Ng of Northern Arizona University,
                   this manual includes solutions for end-of-section and end-of-chapter problems, answers to case
                   questions, where applicable, and teaching tips for each chapter. Electronic solutions are provided in
                   PDF and Word formats.
                   Lecture PowerPoint Presentations—A PowerPoint presentation, created by Professor Patrick
                   Schur of Miami University, is available for each chapter. The PowerPoint slides provide an instruc-
                   tor with individual lecture outlines to accompany the text. The slides include many of the figures
                   and tables from the text. Instructors can use these lecture notes as is or can easily modify the notes
                   to reflect specific presentation needs.
                   Test Item File—Created by Professor Pin Tian Ng of Northern Arizona University, the Test Item
                   File contains true/false, multiple-choice, fill-in, and problem-solving questions based on the defini-
                   tions, concepts, and ideas developed in each chapter of the text.
                   TestGen—The computerized TestGen package allows instructors to customize, save, and generate
                   classroom tests. The test program permits instructors to edit, add, and delete questions from the test
                   bank; edit existing graphics and create new graphics; analyze test results; and organize a database of
                   test and student results. This software provides ease of use and extensive flexibility, and it provides
                   many options for organizing and displaying tests, along with search and sort features. The software
                   and the test banks can be downloaded from the Instructor’s Resource Center.
                   MathXL for Statistics—MathXL for Statistics is a powerful online homework, tutorial, and assess-
                   ment system that accompanies Pearson Education statistics textbooks. With MathXL for Statistics,
                   instructors can create, edit, and assign online homework and tests using algorithmically generated
                   exercises correlated at the objective level to the textbook. They can also create and assign their own
                   online exercises and import TestGen tests for added flexibility. All student work is tracked in
                            ’s
                   MathXL online grade book. Students can take chapter tests in MathXL and receive personalized
                   study plans based on their test results. Each study plan diagnoses weaknesses and links the student
                   directly to tutorial exercises for the objectives he or she needs to study and retest. Students can also
                   access supplemental animations and video clips directly from selected exercises. MathXL for
                   Statistics is available to qualified adopters. For more information, visit www.mathxl.com or con-
                   tact your sales representative.

                   MyStatLab—Part of the MyMathLab and MathXL product family, MyStatLab is a text-specific,
                   easily customizable online course that integrates interactive multimedia instruction with textbook
                   content. MyStatLab gives you the tools you need to deliver all or a portion of your course online,
                   whether your students are in a lab setting or working from home. The latest version of MyStatLab
                   offers a new, intuitive design that features more direct access to MathXL for Statistics pages
                   (Gradebook, Homework & Test Manager, Home Page Manager, etc.) and provides enhanced func-
                   tionality for communicating with students and customizing courses. Other key features include:
                       • Assessment manager An easy-to-use assessment manager lets instructors create online
                         homework, quizzes, and tests that are automatically graded and correlated directly to your
                         textbook. Assignments can be created using a mix of questions from the MyStatLab exercise
                         bank, instructor-created custom exercises, and/or TestGen test items.
                       • Grade book Designed specifically for mathematics and statistics, the MyStatLab grade
                         book automatically tracks students’ results and gives you control over how to calculate final
                         grades. You can also add offline (paper-and-pencil) grades to the grade book.
                       • MathXL Exercise Builder You can use the MathXL Exercise Builder to create static and
                         algorithmic exercises for your online assignments. A library of sample exercises provides an
                         easy starting point for creating questions, and you can also create questions from scratch.
                       • eText-MathXL for Statistics Full Integration Students using appropriate mobile devices
                         can use your eText annotations and highlights for each course, and iPAd users can download
                                                                                                PREFACE      xxix

                     a free app that allows them access to the Do Homework, Take a Test, and Study Plan pages of
                     their course.
                   • “Ask the Publisher” Link in “Ask My Instructor” Email You can easily notify the con-
                     tent team of any irregularities with specific questions by using the “Ask the Publisher” func-
                     tionality in the “Ask My Instructor” emails you receive from students.
                   • Tracking Time Spent on Media Because the latest version of MyStatLab requires students
                     to explicitly click a “Submit” button after viewing the media for their assignments, you will
                     be able to track how long students are spending on each media file.
              Palisade Corporation software—Palisade Corporation, the maker of the market-leading risk and
              decision analysis Excel add-ins, @RISK and the DecisionTools® Suite, provides special academic
              versions of its software. Its flagship product, @RISK, debuted in 1987 and performs risk analysis
              using Monte Carlo simulation. With an estimated 150,000 users, Palisade software can be found in
              more than 100 countries and has been translated into five languages.
                   @RISK and the DecisionTools Suite are used widely in undergraduate and graduate business
              programs worldwide and can be bundled with this textbook. To download a trial version of @RISK
              software, visit www.palisade.com/academic/.


Acknowledgments
              We are extremely grateful to the Biometrika Trustees, American Cyanamid Company, the RAND
              Corporation, and the American Society for Testing and Materials for their kind permission to pub-
              lish various tables in Appendix E, and the American Statistical Association for its permission to
              publish diagrams from the American Statistician. Also, we are grateful to Professors George A.
              Johnson and Joanne Tokle of Idaho State University and Ed Conn, Mountain States Potato
              Company, for their kind permission to incorporate parts of their work as our Mountain States Potato
              Company case in Chapter 15.


A Note of Thanks
              We would like to thank Kevin Caskey, SUNY–New Paltz; Zhi Min Huang, Adelphi University;
              David Huff, Wayne State University; Eugene Jones, Ohio State University; Glen Miller, Piedmont
              College; Angela Mitchell, Wilmington College; Daniel Montgomery, Delta State University;
              Patricia Mullins, University of Wisconsin–Madison; Robert Pred, Temple University; Gary Smith,
              Florida State University; and Robert Wharton, Fordham University for their comments, which have
              made this a better book.
                   We would especially like to thank Chuck Synovec, Mary Kate Murray, Jason Calcano, Judy
              Leale, Anne Fahlgren, Melinda Jensen, and Kerri Tomasso of the editorial, marketing, and produc-
              tion teams at Prentice Hall. We would like to thank our statistical reader and accuracy checker Annie
              Puciloski for her diligence in checking our work; Susan Pariseau, Merrimack College, for assisting
              in the reading of the page proofs; Kitty Wilson for her copyediting; Lori Cavanaugh for her proof-
              reading; and Jen Carley of PreMediaGlobal for her work in the production of this text.
                   Finally, we would like to thank our families for their patience, understanding, love, and assis-
              tance in making this book a reality. It is to them that we dedicate this book.


Concluding Remarks
              We have gone to great lengths to make this text both pedagogically sound and error free. If you have
              any suggestions or require clarification about any of the material, or if you find any errors, please
              contact us at davidlevine@davidlevinestatistics.com. Include the phrase “BBS edition 12” in the
              subject line of your e-mail. For technical support for PHStat2 beyond what is presented in the
              appendices and in the PHStat2 readme file that accompanies PHStat2, visit the PHStat2 website,
              www.pearsonhighered.com/phstat and click on the Contact Pearson Technical Support link.

                                                                                               Mark L. Berenson
                                                                                                 David M. Levine
                                                                                             Timothy C. Krehbiel
     Basic Business
Statistics: Concepts and
      Applications
         TWELFTH EDITION

				
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