- 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 16 and 17: xiv Contents Forward Selection 572
- 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: UNIT I INTRODUCTION The study 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
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- Page 57 and 58: 2.3 Qualitative Data Graphs 27 2.9
- Page 59 and 60: 2.3 Qualitative Data Graphs 29 FIGU
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- Page 63 and 64: 2.4 Graphical Depiction of Two-Vari
- Page 65 and 66: Problems 35 Pie Charts for World Oi
- Page 67 and 68: Supplementary Problems 37 2.19 Cons
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52 Chapter 3 Descriptive Statistics
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54 Chapter 3 Descriptive Statistics
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56 Chapter 3 Descriptive Statistics
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ƒ ƒ 58 Chapter 3 Descriptive Stat
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60 Chapter 3 Descriptive Statistics
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62 Chapter 3 Descriptive Statistics
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64 Chapter 3 Descriptive Statistics
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66 Chapter 3 Descriptive Statistics
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68 Chapter 3 Descriptive Statistics
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70 Chapter 3 Descriptive Statistics
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72 Chapter 3 Descriptive Statistics
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74 Chapter 3 Descriptive Statistics
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76 Chapter 3 Descriptive Statistics
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78 Chapter 3 Descriptive Statistics
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80 Chapter 3 Descriptive Statistics
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82 Chapter 3 Descriptive Statistics
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84 Chapter 3 Descriptive Statistics
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86 Chapter 3 Descriptive Statistics
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88 Chapter 3 Descriptive Statistics
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90 Chapter 3 Descriptive Statistics
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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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220 Chapter 7 Sampling and Sampling
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222 Chapter 7 Sampling and Sampling
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224 Chapter 7 Sampling and Sampling
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226 Chapter 7 Sampling and Sampling
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228 Chapter 7 Sampling and Sampling
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230 Chapter 7 Sampling and Sampling
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232 Chapter 7 Sampling and Sampling
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234 Chapter 7 Sampling and Sampling
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236 Chapter 7 Sampling and Sampling
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238 Chapter 7 Sampling and Sampling
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240 Chapter 7 Sampling and Sampling
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242 Chapter 7 Sampling and Sampling
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244 Chapter 7 Sampling and Sampling
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246 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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254 Chapter 8 Statistical Inference
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256 Chapter 8 Statistical Inference
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258 Chapter 8 Statistical Inference
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260 Chapter 8 Statistical Inference
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262 Chapter 8 Statistical Inference
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264 Chapter 8 Statistical Inference
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266 Chapter 8 Statistical Inference
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268 Chapter 8 Statistical Inference
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270 Chapter 8 Statistical Inference
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272 Chapter 8 Statistical Inference
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274 Chapter 8 Statistical Inference
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276 Chapter 8 Statistical Inference
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278 Chapter 8 Statistical Inference
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280 Chapter 8 Statistical Inference
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282 Chapter 8 Statistical Inference
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284 Chapter 8 Statistical Inference
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286 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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9.1 Introduction to Hypothesis Test
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9.1 Introduction to Hypothesis Test
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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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9.2 Testing Hypotheses About a Popu
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9.2 Testing Hypotheses About a Popu
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9.2 Testing Hypotheses About a Popu
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Problems 307 one-tailed hypothesis,
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9.3 Testing Hypotheses About a Popu
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9.3 Testing Hypotheses About a Popu
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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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9.4 Testing Hypotheses About a Prop
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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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9.6 Solving for Type II Errors 327
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9.6 Solving for Type II Errors 329
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9.6 Solving for Type II Errors 331
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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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10.1 Hypothesis Testing and Confide
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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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10.2 Hypothesis Testing and Confide
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10.2 Hypothesis Testing and Confide
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10.2 Hypothesis Testing and Confide
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10.2 Hypothesis Testing and Confide
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Problems 363 Test your conjecture,
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10.3 Statistical Inferences for Two
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10.3 Statistical Inferences for Two
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10.3 Statistical Inferences for Two
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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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10.4 Statistical Inferences about T
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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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10.5 Testing Hypotheses about Two P
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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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406 Chapter 11 Analysis of Variance
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408 Chapter 11 Analysis of Variance
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410 Chapter 11 Analysis of Variance
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412 Chapter 11 Analysis of Variance
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414 Chapter 11 Analysis of Variance
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416 Chapter 11 Analysis of Variance
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418 Chapter 11 Analysis of Variance
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420 Chapter 11 Analysis of Variance
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422 Chapter 11 Analysis of Variance
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424 Chapter 11 Analysis of Variance
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426 Chapter 11 Analysis of Variance
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428 Chapter 11 Analysis of Variance
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430 Chapter 11 Analysis of Variance
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432 Chapter 11 Analysis of Variance
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434 Chapter 11 Analysis of Variance
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436 Chapter 11 Analysis of Variance
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438 Chapter 11 Analysis of Variance
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440 Chapter 11 Analysis of Variance
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442 Chapter 11 Analysis of Variance
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444 Chapter 11 Analysis of Variance
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446 Chapter 11 Analysis of Variance
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448 Chapter 11 Analysis of Variance
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450 Chapter 11 Analysis of Variance
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452 Chapter 11 Analysis of Variance
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454 Chapter 11 Analysis of Variance
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456 Chapter 11 Analysis of Variance
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458 Chapter 11 Analysis of Variance
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460 Chapter 11 Analysis of Variance
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UNIT IV REGRESSION ANALYSIS AND FOR
- Page 495 and 496:
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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12.7 Hypothesis Tests for the Slope
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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
- Page 561 and 562:
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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550 Chapter 14 Building Multiple Re
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552 Chapter 14 Building Multiple Re
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554 Chapter 14 Building Multiple Re
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556 Chapter 14 Building Multiple Re
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558 Chapter 14 Building Multiple Re
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560 Chapter 14 Building Multiple Re
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562 Chapter 14 Building Multiple Re
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564 Chapter 14 Building Multiple Re
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566 Chapter 14 Building Multiple Re
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568 Chapter 14 Building Multiple Re
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570 Chapter 14 Building Multiple Re
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572 Chapter 14 Building Multiple Re
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574 Chapter 14 Building Multiple Re
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576 Chapter 14 Building Multiple Re
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578 Chapter 14 Building Multiple Re
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580 Chapter 14 Building Multiple Re
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582 Chapter 14 Building Multiple Re
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584 Chapter 14 Building Multiple Re
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586 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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592 Chapter 15 Time-Series Forecast
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594 Chapter 15 Time-Series Forecast
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596 Chapter 15 Time-Series Forecast
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598 Chapter 15 Time-Series Forecast
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600 Chapter 15 Time-Series Forecast
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602 Chapter 15 Time-Series Forecast
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604 Chapter 15 Time-Series Forecast
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606 Chapter 15 Time-Series Forecast
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608 Chapter 15 Time-Series Forecast
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610 Chapter 15 Time-Series Forecast
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612 Chapter 15 Time-Series Forecast
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614 Chapter 15 Time-Series Forecast
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616 Chapter 15 Time-Series Forecast
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618 Chapter 15 Time-Series Forecast
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620 Chapter 15 Time-Series Forecast
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622 Chapter 15 Time-Series Forecast
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624 Chapter 15 Time-Series Forecast
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626 Chapter 15 Time-Series Forecast
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628 Chapter 15 Time-Series Forecast
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630 Chapter 15 Time-Series Forecast
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632 Chapter 15 Time-Series Forecast
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634 Chapter 15 Time-Series Forecast
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636 Chapter 15 Time-Series Forecast
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638 Chapter 15 Time-Series Forecast
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640 Chapter 15 Time-Series Forecast
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642 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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648 Chapter 16 Analysis of Categori
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650 Chapter 16 Analysis of Categori
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652 Chapter 16 Analysis of Categori
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654 Chapter 16 Analysis of Categori
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656 Chapter 16 Analysis of Categori
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658 Chapter 16 Analysis of Categori
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660 Chapter 16 Analysis of Categori
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662 Chapter 16 Analysis of Categori
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664 Chapter 16 Analysis of Categori
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666 Chapter 16 Analysis of Categori
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668 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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674 Chapter 17 Nonparametric Statis
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676 Chapter 17 Nonparametric Statis
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678 Chapter 17 Nonparametric Statis
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680 Chapter 17 Nonparametric Statis
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682 Chapter 17 Nonparametric Statis
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684 Chapter 17 Nonparametric Statis
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686 Chapter 17 Nonparametric Statis
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688 Chapter 17 Nonparametric Statis
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690 Chapter 17 Nonparametric Statis
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692 Chapter 17 Nonparametric Statis
- Page 724 and 725:
694 Chapter 17 Nonparametric Statis
- Page 726 and 727:
696 Chapter 17 Nonparametric Statis
- Page 728 and 729:
698 Chapter 17 Nonparametric Statis
- Page 730 and 731:
700 Chapter 17 Nonparametric Statis
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702 Chapter 17 Nonparametric Statis
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704 Chapter 17 Nonparametric Statis
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706 Chapter 17 Nonparametric Statis
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708 Chapter 17 Nonparametric Statis
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710 Chapter 17 Nonparametric Statis
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712 Chapter 17 Nonparametric Statis
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714 Chapter 17 Nonparametric Statis
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716 Chapter 17 Nonparametric Statis
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718 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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18.1 Introduction to Quality Contro
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18.1 Introduction to Quality Contro
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18.1 Introduction to Quality Contro
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18.1 Introduction to Quality Contro
- Page 763 and 764:
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
- Page 769 and 770:
18.3 Control Charts 739 charts are
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18.3 Control Charts 741 UCL and LCL
- Page 773 and 774:
18.3 Control Charts 743 Using the s
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18.3 Control Charts 745 Compute R R
- Page 777 and 778:
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
- Page 787 and 788:
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
- 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 and 800:
Appendix A Tables 769 TABLE A.2 Bin
- Page 801 and 802:
Appendix A Tables 771 TABLE A.2 Bin
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Appendix A Tables 773 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
- Page 809 and 810:
Appendix A Tables 779 TABLE A.4 The
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Appendix A Tables 781 TABLE A.6 Cri
- Page 813 and 814:
Appendix A Tables 783 TABLE A.7 Per
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Appendix A Tables 785 TABLE A.7 Per
- Page 817 and 818:
Appendix A Tables 787 TABLE A.7 Per
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Appendix A Tables 789 TABLE A.7 Per
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Appendix A Tables 791 TABLE A.7 Per
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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
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APPENDIX B Answers to Selected Odd-
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Appendix B Answers to Selected Odd-
- Page 839 and 840:
Appendix B Answers to Selected Odd-
- Page 841 and 842:
Appendix B Answers to Selected Odd-
- Page 843 and 844:
Appendix B Answers to Selected Odd-
- Page 845 and 846:
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
- Page 856 and 857:
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,
- Page 862 and 863:
832 Index Populations accessing for
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834 Index Samples defined, 5 depend
- Page 866:
836 Index grouped data versus, 17-1
- Page 869 and 870:
Decision Making at the CEO Level CE
- Page 871 and 872:
19.1 The Decision Table and Decisio
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19.2 Decision Making Under Uncertai
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19.2 Decision Making Under Uncertai
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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
- Page 883 and 884:
19.3 Decision Making Under Risk C19
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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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19.4 Revising Probabilities in Ligh
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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