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xiv Contents Forward Selection 572 Backward Elimination 572 14.4 Multicollinearity 576 Summary 580 Key Terms 581 Formulas 581 Supplementary Problems 581 Analyzing the Databases 584 Case: Virginia Semiconductor 585 Using the Computer 586 15 Time-Series Forecasting and Index Numbers 588 Decision Dilemma: Forecasting Air Pollution 589 15.1 Introduction to Forecasting 590 Time-Series Components 590 The Measurement of Forecasting Error 591 Error 591 Mean Absolute Deviation (MAD) 591 Mean Square Error (MSE) 592 15.2 Smoothing Techniques 594 Naïve Forecasting Models 594 Averaging Models 595 Simple Averages 595 Moving Averages 595 Weighted Moving Averages 597 Exponential Smoothing 599 15.3 Trend Analysis 604 Linear Regression Trend Analysis 604 Regression Trend Analysis Using Quadratic Models 606 Holt’s Two-Parameter Exponential Smoothing Method 609 15.4 Seasonal Effects 611 Decomposition 611 Finding Seasonal Effects with the Computer 614 Winters’ Three-Parameter Exponential Smoothing Method 614 15.5 Autocorrelation and Autoregression 616 Autocorrelation 616 Ways to Overcome the Autocorrelation Problem 619 Addition of Independent Variables 619 Transforming Variables 620 Autoregression 620 15.6 Index Numbers 623 Simple Index Numbers 624 Unweighted Aggregate Price Index Numbers 624 Weighted Aggregate Price Index Numbers 625 Laspeyres Price Index 626 Paasche Price Index 627 Summary 632 Key Terms 633 Formulas 633 Supplementary Problems 633 Analyzing the Databases 638 Case: Debourgh Manufacturing Company 639 Using the Computer 640 UNIT V NONPARAMETRIC STATISTICS AND QUALITY 16 Analysis of Categorical Data 644 Decision Dilemma: Selecting Suppliers in the Electronics Industry 645 16.1 Chi-Square Goodness-of-Fit Test 646 Testing a Population Proportion by Using the Chi-Square Goodness-of-Fit Test as an Alternative Technique to the z Test 652 16.2 Contingency Analysis: Chi-Square Test of Independence 656 Summary 666 Key Terms 666 Formulas 666 Supplementary Problems 666 Analyzing the Databases 668 Case: Foot Locker in the Shoe Mix 668 Using the Computer 669 17 Nonparametric Statistics 670 Decision Dilemma: How Is the Doughnut Business? 671 17.1 Runs Test 673 Small-Sample Runs Test 674 Large-Sample Runs Test 675 17.2 Mann-Whitney U Test 678 Small-Sample Case 678 Large-Sample Case 680 17.3 Wilcoxon Matched-Pairs Signed Rank Test 686 Small-Sample Case (n 15) 686 Large-Sample Case (n 15) 688 17.4 Kruskal-Wallis Test 694 17.5 Friedman Test 699 17.6 Spearman’s Rank Correlation 705 Summary 710 Key Terms 711 Formulas 711
Contents xv Supplementary Problems 711 Analyzing the Databases 716 Case: Schwinn 717 Using the Computer 718 18 Statistical Quality Control 720 Decision Dilemma: Italy’s Piaggio Makes a Comeback 721 18.1 Introduction to Quality Control 722 What Is Quality Control? 722 Total Quality Management 723 Deming’s 14 Points 724 Quality Gurus 725 Six Sigma 725 Design for Six Sigma 727 Lean Manufacturing 727 Some Important Quality Concepts 727 Benchmarking 728 Just-in-Time Inventory Systems 728 Reengineering 729 Failure Mode and Effects Analysis 730 Poka-Yoke 731 Quality Circles and Six Sigma Teams 731 18.2 Process Analysis 733 Flowcharts 733 Pareto Analysis 734 Cause-and-Effect (Fishbone) Diagrams 735 Control Charts 736 Check Sheets or Checklists 737 Histogram 738 Scatter Chart or Scatter Diagram 738 18.3 Control Charts 739 Variation 740 Types of Control Charts 740 x Chart 740 R Charts 744 p Charts 745 c Charts 748 Interpreting Control Charts 750 Summary 756 Key Terms 757 Formulas 757 Supplementary Problems 758 Analyzing the Databases 761 Case: Robotron-ELOTHERM 762 Using the Computer 763 APPENDICES A Tables 765 B Answers to Selected Odd-Numbered Quantitative Problems 805 GLOSSARY 815 INDEX 825 The following materials are available at www.wiley.com/college/black 19 Decision Analysis C19-2 Decision Dilemma: Decision Making at the CEO Level C19-3 19.1 The Decision Table and Decision Making Under Certainty C19-4 Decision Table C19-4 Decision Making Under Certainty C19-5 19.2 Decision Making Under Uncertainty C19-6 Maximax Criterion C19-6 Maximin Criterion C19-6 Hurwicz Criterion C19-7 Minimax Regret C19-9 19.3 Decision Making Under Risk C19-14 Decision Trees C19-14 Expected Monetary Value (EMV) C19-14 Expected Value of Perfect Information C19-18 Utility C19-19 19.4 Revising Probabilities in Light of Sample Information C19-22 Expected Value of Sample Information C19-25 Summary C19-32 Key Terms C19-33 Formula C19-33 Supplementary Problems C19-33 Analyzing the Databases C19-36 Case: Fletcher-Terry: On the Cutting Edge C19-36 SUPPLEMENTS 1 Summation Notation S1-1 2 Derivation of Simple Regression Formulas for Slope and y Intercept S2-1 3 Advanced Exponential Smoothing S3-1 Exponential Smoothing with Trend Effects: Holt’s Method S3-1 Exponential Smoothing with Both Trend and Seasonality: Winter’s Method S3-2 Some Practice Problems S3-5
Page 3 and 4: With WileyPLUS: This online teachin
Page 5: 6 TH EDITION Business Statistics Fo
Page 8 and 9: Vice President & Publisher George H
Page 10 and 11: BRIEF CONTENTS UNIT I UNIT II UNIT
Page 12 and 13: x Contents 3.5 Descriptive Statisti
Page 14 and 15: xii Contents Statistical Hypotheses
Page 19 and 20: PREFACE The sixth edition of Busine
Page 21 and 22: Preface xix all of the inferential
Page 23 and 24: Preface xxi very limited access to
Page 25 and 26: Preface xxiii Interpreting the Outp
Page 27: Preface xxv ACKNOWLEDGMENTS John Wi
Page 31 and 32: UNIT I INTRODUCTION The study of bu
Page 33 and 34: Statistics Describe the State of Bu
Page 35 and 36: 1.2 Basic Statistical Concepts 5 In
Page 37 and 38: 1.3 Data Measurement 7 FIGURE 1.1 P
Page 39 and 40: 1.3 Data Measurement 9 In addition,
Page 41 and 42: 1.3 Data Measurement 11 Statistical
Page 43 and 44: Analyzing the Databases 13 1.3 Give
Page 45 and 46: Case 15 ASSIGNMENT Use the database
Page 47 and 48: Energy Consumption Around the World
Page 49 and 50: 2.1 Frequency Distributions 19 TABL
Page 51 and 52: 2.2 Quantitative Data Graphs 21 cla
Page 53 and 54: 2.2 Quantitative Data Graphs 23 FIG
Page 55 and 56: 2.2 Quantitative Data Graphs 25 FIG
Page 57 and 58: 2.3 Qualitative Data Graphs 27 2.9
Page 59 and 60: 2.3 Qualitative Data Graphs 29 FIGU
Page 61 and 62: 2.3 Qualitative Data Graphs 31 STAT
Page 63 and 64: 2.4 Graphical Depiction of Two-Vari
Page 65 and 66: Problems 35 Pie Charts for World Oi
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Supplementary Problems 37 2.19 Cons
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Supplementary Problems 39 include t
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Using the Computer 41 In 1983, the
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Using the Computer 43 ■ ■ ■ t
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CHAPTER 3 Descriptive Statistics LE
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48 Chapter 3 Descriptive Statistics
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ƒ ƒ 58 Chapter 3 Descriptive Stat
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CHAPTER 4 Probability LEARNING OBJE
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94 Chapter 4 Probability FIGURE 4.1
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96 Chapter 4 Probability Subjective
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98 Chapter 4 Probability FIGURE 4.3
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100 Chapter 4 Probability THE mn CO
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102 Chapter 4 Probability FIGURE 4.
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104 Chapter 4 Probability TABLE 4.2
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106 Chapter 4 Probability By the ge
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108 Chapter 4 Probability P (neithe
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110 Chapter 4 Probability 4.10 Use
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ƒ ƒ 112 Chapter 4 Probability ran
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114 Chapter 4 Probability DEMONSTRA
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116 Chapter 4 Probability 4.21 A st
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ƒ 118 Chapter 4 Probability The se
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ƒ 120 Chapter 4 Probability STATIS
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122 Chapter 4 Probability the South
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124 Chapter 4 Probability TABLE 4.8
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126 Chapter 4 Probability Event Pri
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128 Chapter 4 Probability ETHICAL C
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130 Chapter 4 Probability TESTING Y
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132 Chapter 4 Probability 4.49 In a
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UNIT II DISTRIBUTIONS AND SAMPLING
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Life with a Cell Phone As early as
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5.2 Describing a Discrete Distribut
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5.2 Describing a Discrete Distribut
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5.3 Binomial Distribution 143 5.3 T
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5.3 Binomial Distribution 145 selec
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5.3 Binomial Distribution 147 DEMON
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ƒ 5.3 Binomial Distribution 149 TA
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5.3 Binomial Distribution 151 FIGUR
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Problems 153 5.8 Use the probabilit
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5.4 Poisson Distribution 155 time i
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5.4 Poisson Distribution 157 Soluti
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5.4 Poisson Distribution 159 FIGURE
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5.4 Poisson Distribution 161 The Po
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Problems 163 data set as a basis fo
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5.5 Hypergeometric Distribution 165
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Problems 167 5.5 PROBLEMS 5.27 Comp
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Key Terms 169 problem, but it can b
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Supplementary Problems 171 5.36 Use
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Supplementary Problems 173 Suppose
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Case 175 ANALYZING THE DATABASES se
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Using the Computer 177 ■ in a col
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The Cost of Human Resources What is
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6.1 The Uniform Distribution 181 FI
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6.1 The Uniform Distribution 183 DE
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6.2 Normal Distribution 185 FIGURE
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6.2 Normal Distribution 187 TABLE 6
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6.2 Normal Distribution 189 This pr
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6.2 Normal Distribution 191 The pro
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6.2 Normal Distribution 193 DEMONST
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Problems 195 6.9 According to the I
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6.3 Using the Normal Curve to Appro
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6.3 Using the Normal Curve to Appro
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Problems 201 The answer obtained by
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6.4 Exponential Distribution 203 FI
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Problems 205 TABLE 6.6 Excel and Mi
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Summary 207 The area associated wit
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Supplementary Problems 209 6.36 Wor
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Supplementary Problems 211 availabi
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Using the Computer 213 that sales a
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CHAPTER 7 Sampling and Sampling Dis
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218 Chapter 7 Sampling and Sampling
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248 Making Inferences About Populat
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CHAPTER 8 Statistical Inference: Es
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252 Chapter 8 Statistical Inference
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Word-of-Mouth Business Referrals an
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9.1 Introduction to Hypothesis Test
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9.2 Testing Hypotheses About a Popu
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Problems 307 one-tailed hypothesis,
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Problems 313 Excel does not have a
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9.4 Testing Hypotheses About a Prop
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9.5 Testing Hypotheses About a Vari
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Problems 323 DEMONSTRATION PROBLEM
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9.6 Solving for Type II Errors 325
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Problems 333 9.40 The New York Stoc
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Supplementary Problems 335 with an
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Supplementary Problems 337 and she
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Case 339 CASE FRITO-LAY TARGETS THE
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Using the Computer 341 ■ To begin
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Online Shopping The use of online s
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Proportions 2-Samples Chapter 10 St
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10.1 Hypothesis Testing and Confide
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Problems 353 10.2 Use the following
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Problems 363 Test your conjecture,
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10.3 Statistical Inferences for Two
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Problems 373 Client Before After 1
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10.4 Statistical Inferences about T
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Problems 381 b. H 0 : p 1 - p 2 = 0
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10.5 Testing Hypotheses about Two P
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Problems 389 City 1 City 2 3.43 3.3
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Summary 391 SUMMARY Business resear
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Supplementary Problems 393 TESTING
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Supplementary Problems 395 machine
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Case 397 ANALYZING THE DATABASES 1.
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Using the Computer 399 ■ ■ add-
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CHAPTER 11 Analysis of Variance and
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404 Chapter 11 Analysis of Variance
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UNIT IV REGRESSION ANALYSIS AND FOR
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Predicting International Hourly Wag
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12.1 Correlation 467 FIGURE 12.1 Fi
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12.2 Introduction to Simple Regress
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12.3 Determining the Equation of th
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12.3 Determining the Equation of th
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Problems 475 Using these values, th
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12.4 Residual Analysis 477 Raw Stee
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12.4 Residual Analysis 479 FIGURE 1
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12.4 Residual Analysis 481 DEMONSTR
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Problems 483 Cost of Milk (per gall
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12.5 Standard Error of the Estimate
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12.6 Coefficient of Determination 4
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12.7 Hypothesis Tests for the Slope
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12.8 Estimation 495 result, yieldin
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12.8 Estimation 497 FIGURE 12.16 Mi
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12.9 Using Regression to Develop a
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12.9 Using Regression to Develop a
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Problems 503 Solution Shown here is
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12.10 Interpreting the Output 505 F
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12.10 Interpreting the Output 507 S
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Supplementary Problems 509 KEY TERM
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Supplementary Problems 511 publishe
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Case 513 Frequency 7 6 5 4 3 2 1 0
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Using the Computer 515 Cumulative H
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Are You Going to Hate Your New Job?
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13.1 The Multiple Regression Model
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13.1 The Multiple Regression Model
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Problems 523 Solution The following
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13.2 Significance Tests of the Regr
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13.2 Significance Tests of the Regr
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Problems 529 13.9 Using the data in
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13.3 Residuals, Standard Error of t
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13.3 Residuals, Standard Error of t
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13.4 Interpreting Multiple Regressi
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13.4 Interpreting Multiple Regressi
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Summary 539 SUMMARY OUTPUT Regressi
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Supplementary Problems 541 TESTING
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Case 543 ANALYZING THE DATABASES 1.
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CHAPTER 14 Building Multiple Regres
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548 Chapter 14 Building Multiple Re
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CHAPTER 15 Time-Series Forecasting
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590 Chapter 15 Time-Series Forecast
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CHAPTER 16 Analysis of Categorical
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646 Chapter 16 Analysis of Categori
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CHAPTER 17 Nonparametric Statistics
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672 Chapter 17 Nonparametric Statis
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Italy’s Piaggio Makes a Comeback
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18.1 Introduction to Quality Contro
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18.2 Process Analysis 733 18.2 PROC
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18.2 Process Analysis 735 FIGURE 18
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18.2 Process Analysis 737 FIGURE 18
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18.3 Control Charts 739 charts are
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18.3 Control Charts 741 UCL and LCL
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18.3 Control Charts 743 Using the s
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18.3 Control Charts 745 Compute R R
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18.3 Control Charts 747 Sample n Ou
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18.3 Control Charts 749 In computin
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18.3 Control Charts 751 below the c
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Problems 753 18.6 A machine operato
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Problems 755 a. 125 X bar Chart 3.0
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Formulas 757 identifying the effect
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Supplementary Problems 759 five con
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Analyzing the Databases 761 12.5 X
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Using the Computer 763 Sample Mean
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APPENDIX A Tables Table A.1: Random
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Appendix A Tables 767 TABLE A.2 Bin
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Appendix A Tables 775 TABLE A.3 Poi
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Appendix A Tables 777 TABLE A.3 Poi
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Appendix A Tables 793 TABLE A.9 Cri
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Appendix A Tables 797 n 2 n 1 = .02
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Appendix A Tables 799 TABLE A.13 p-
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Appendix A Tables 801 TABLE A.13 p-
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Appendix A Tables 803 TABLE A.14 Cr
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APPENDIX B Answers to Selected Odd-
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Appendix B Answers to Selected Odd-
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GLOSSARY A a posteriori After the e
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Glossary 817 decision table A matri
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Glossary 819 the statistic below th
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Glossary 821 ratio level data Highe
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Glossary 823 W weighted aggregate p
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826 Index Centerline. See also Cont
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828 Index DMAIC (Define, Measure, A
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830 Index Law of improbable events,
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832 Index Populations accessing for
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834 Index Samples defined, 5 depend
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836 Index grouped data versus, 17-1
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Decision Making at the CEO Level CE
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19.1 The Decision Table and Decisio
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19.2 Decision Making Under Uncertai
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Problems C19-13 d. Compute an oppor
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19.3 Decision Making Under Risk C19
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Problems C19-21 Much information ha
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19.4 Revising Probabilities in Ligh
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Problems C19-29 The worth of the sa
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Problems C19-31 Decision Making at
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Supplementary Problems C19-33 for e
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Supplementary Problems C19-35 Decis
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Case C19-37 Following these initiat
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Critical Values from the t Distribu
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