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770 Appendix A Tables TABLE A.2 Binomial Probability Distribution (Continued) n 14 Probability x .1 .2 .3 .4 .5 .6 .7 .8 .9 0 .229 .044 .007 .001 .000 .000 .000 .000 .000 1 .356 .154 .041 .007 .001 .000 .000 .000 .000 2 .257 .250 .113 .032 .006 .001 .000 .000 .000 3 .114 .250 .194 .085 .022 .003 .000 .000 .000 4 .035 .172 .229 .155 .061 .014 .001 .000 .000 5 .008 .086 .196 .207 .122 .041 .007 .000 .000 6 .001 .032 .126 .207 .183 .092 .023 .002 .000 7 .000 .009 .062 .157 .209 .157 .062 .009 .000 8 .000 .002 .023 .092 .183 .207 .126 .032 .001 9 .000 .000 .007 .041 .122 .207 .196 .086 .008 10 .000 .000 .001 .014 .061 .155 .229 .172 .035 11 .000 .000 .000 .003 .022 .085 .194 .250 .114 12 .000 .000 .000 .001 .006 .032 .113 .250 .257 13 .000 .000 .000 .000 .001 .007 .041 .154 .356 14 .000 .000 .000 .000 .000 .001 .007 .044 .229 n 15 Probability x .1 .2 .3 .4 .5 .6 .7 .8 .9 0 .206 .035 .005 .000 .000 .000 .000 .000 .000 1 .343 .132 .031 .005 .000 .000 .000 .000 .000 2 .267 .231 .092 .022 .003 .000 .000 .000 .000 3 .129 .250 .170 .063 .014 .002 .000 .000 .000 4 .043 .188 .219 .127 .042 .007 .001 .000 .000 5 .010 .103 .206 .186 .092 .024 .003 .000 .000 6 .002 .043 .147 .207 .153 .061 .012 .001 .000 7 .000 .014 .081 .177 .196 .118 .035 .003 .000 8 .000 .003 .035 .118 .196 .177 .081 .014 .000 9 .000 .001 .012 .061 .153 .207 .147 .043 .002 10 .000 .000 .003 .024 .092 .186 .206 .103 .010 11 .000 .000 .001 .007 .042 .127 .219 .188 .043 12 .000 .000 .000 .002 .014 .063 .170 .250 .129 13 .000 .000 .000 .000 .003 .022 .092 .231 .267 14 .000 .000 .000 .000 .000 .005 .031 .132 .343 15 .000 .000 .000 .000 .000 .000 .005 .035 .206
Appendix A Tables 771 TABLE A.2 Binomial Probability Distribution (Continued) n 16 Probability x .1 .2 .3 .4 .5 .6 .7 .8 .9 0 .185 .028 .003 .000 .000 .000 .000 .000 .000 1 .329 .113 .023 .003 .000 .000 .000 .000 .000 2 .275 .211 .073 .015 .002 .000 .000 .000 .000 3 .142 .246 .146 .047 .009 .001 .000 .000 .000 4 .051 .200 .204 .101 .028 .004 .000 .000 .000 5 .014 .120 .210 .162 .067 .014 .001 .000 .000 6 .003 .055 .165 .198 .122 .039 .006 .000 .000 7 .000 .020 .101 .189 .175 .084 .019 .001 .000 8 .000 .006 .049 .142 .196 .142 .049 .006 .000 9 .000 .001 .019 .084 .175 .189 .101 .020 .000 10 .000 .000 .006 .039 .122 .198 .165 .055 .003 11 .000 .000 .001 .014 .067 .162 .210 .120 .014 12 .000 .000 .000 .004 .028 .101 .204 .200 .051 13 .000 .000 .000 .001 .009 .047 .146 .246 .142 14 .000 .000 .000 .000 .002 .015 .073 .211 .275 15 .000 .000 .000 .000 .000 .003 .023 .113 .329 16 .000 .000 .000 .000 .000 .000 .003 .028 .185 n 17 Probability x .1 .2 .3 .4 .5 .6 .7 .8 .9 0 .167 .023 .002 .000 .000 .000 .000 .000 .000 1 .315 .096 .017 .002 .000 .000 .000 .000 .000 2 .280 .191 .058 .010 .001 .000 .000 .000 .000 3 .156 .239 .125 .034 .005 .000 .000 .000 .000 4 .060 .209 .187 .080 .018 .002 .000 .000 .000 5 .017 .136 .208 .138 .047 .008 .001 .000 .000 6 .004 .068 .178 .184 .094 .024 .003 .000 .000 7 .001 .027 .120 .193 .148 .057 .009 .000 .000 8 .000 .008 .064 .161 .185 .107 .028 .002 .000 9 .000 .002 .028 .107 .185 .161 .064 .008 .000 10 .000 .000 .009 .057 .148 .193 .120 .027 .001 11 .000 .000 .003 .024 .094 .184 .178 .068 .004 12 .000 .000 .001 .008 .047 .138 .208 .136 .017 13 .000 .000 .000 .002 .018 .080 .187 .209 .060 14 .000 .000 .000 .000 .005 .034 .125 .239 .156 15 .000 .000 .000 .000 .001 .010 .058 .191 .280 16 .000 .000 .000 .000 .000 .002 .017 .096 .315 17 .000 .000 .000 .000 .000 .000 .002 .023 .167 (Continued)
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With WileyPLUS: This online teachin
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6 TH EDITION Business Statistics Fo
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Vice President & Publisher George H
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BRIEF CONTENTS UNIT I UNIT II UNIT
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x Contents 3.5 Descriptive Statisti
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xii Contents Statistical Hypotheses
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xiv Contents Forward Selection 572
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PREFACE The sixth edition of Busine
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Preface xix all of the inferential
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Preface xxi very limited access to
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Preface xxiii Interpreting the Outp
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Preface xxv ACKNOWLEDGMENTS John Wi
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UNIT I INTRODUCTION The study of bu
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Statistics Describe the State of Bu
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1.2 Basic Statistical Concepts 5 In
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1.3 Data Measurement 7 FIGURE 1.1 P
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1.3 Data Measurement 9 In addition,
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1.3 Data Measurement 11 Statistical
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Analyzing the Databases 13 1.3 Give
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Case 15 ASSIGNMENT Use the database
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Energy Consumption Around the World
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2.1 Frequency Distributions 19 TABL
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2.2 Quantitative Data Graphs 21 cla
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2.2 Quantitative Data Graphs 23 FIG
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2.2 Quantitative Data Graphs 25 FIG
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2.3 Qualitative Data Graphs 27 2.9
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2.3 Qualitative Data Graphs 29 FIGU
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2.3 Qualitative Data Graphs 31 STAT
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2.4 Graphical Depiction of Two-Vari
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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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Page 751 and 752: Italy’s Piaggio Makes a Comeback
Page 753 and 754: 18.1 Introduction to Quality Contro
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Page 765 and 766: 18.2 Process Analysis 735 FIGURE 18
Page 767 and 768: 18.2 Process Analysis 737 FIGURE 18
Page 769 and 770: 18.3 Control Charts 739 charts are
Page 771 and 772: 18.3 Control Charts 741 UCL and LCL
Page 773 and 774: 18.3 Control Charts 743 Using the s
Page 775 and 776: 18.3 Control Charts 745 Compute R R
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Page 779 and 780: 18.3 Control Charts 749 In computin
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Page 783 and 784: Problems 753 18.6 A machine operato
Page 785 and 786: Problems 755 a. 125 X bar Chart 3.0
Page 787 and 788: Formulas 757 identifying the effect
Page 789 and 790: Supplementary Problems 759 five con
Page 791 and 792: Analyzing the Databases 761 12.5 X
Page 793 and 794: Using the Computer 763 Sample Mean
Page 795 and 796: APPENDIX A Tables Table A.1: Random
Page 797 and 798: Appendix A Tables 767 TABLE A.2 Bin
Page 799: Appendix A Tables 769 TABLE A.2 Bin
Page 803 and 804: Appendix A Tables 773 TABLE A.2 Bin
Page 805 and 806: Appendix A Tables 775 TABLE A.3 Poi
Page 807 and 808: Appendix A Tables 777 TABLE A.3 Poi
Page 809 and 810: Appendix A Tables 779 TABLE A.4 The
Page 811 and 812: Appendix A Tables 781 TABLE A.6 Cri
Page 813 and 814: Appendix A Tables 783 TABLE A.7 Per
Page 823 and 824: Appendix A Tables 793 TABLE A.9 Cri
Page 825 and 826: Appendix A Tables 795 TABLE A.10 Cr
Page 827 and 828: Appendix A Tables 797 n 2 n 1 = .02
Page 829 and 830: Appendix A Tables 799 TABLE A.13 p-
Page 831 and 832: Appendix A Tables 801 TABLE A.13 p-
Page 833 and 834: Appendix A Tables 803 TABLE A.14 Cr
Page 835 and 836: APPENDIX B Answers to Selected Odd-
Page 837 and 838: Appendix B Answers to Selected Odd-
Page 845 and 846: GLOSSARY A a posteriori After the e
Page 847 and 848: Glossary 817 decision table A matri
Page 849 and 850: 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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