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| 书名： | 【正版】商务与经济统计方法（英文版·原书第15版）|4730954 |
| 图书定价： | 89元 |
| 图书作者： | （美）道格拉斯 A.林德（Douglas A. Lind）;（美）威廉 G.马歇尔（William G. Marchal）;（美）塞缪尔 A.沃森（Samuel A. Wathen） |
| 出版社： | 机械工业出版社 |
| 出版日期： | 2015/7/1 0:00:00 |
| ISBN号： | 9787111507109 |
| 开本： | 16开 |
| 页数： | 752 |
| 版次： | 15-1 |
| 作者简介 |
| 作者：（美国）道格拉斯 A.林德（Douglas A.Lind） （美国）威廉 G.马歇尔（William G.Marchal） （美国）塞缪尔 A.沃森（Samuel A.Wathen） 译者：聂巧平 叶光 |
| 内容简介 |
| 本书是统计学最的教材之一，为读者深入领会统计概念的含义提供了最有效的工具。本书编排新颖，讲解清晰简洁，结合大量的案例，使统计技术不再枯燥，变得生动有趣，方便读者理解和学习。 本书不仅适用于全国各财经院校统计专业的广大师生，而且为主修经济、财政、金融、市场营销、会计和管理专业的师生提供了一本应用统计技术的指导手册。 |
| 目录 |
| 出版说明 导读 前言 第1章 什么是统计学 1 1.1 引言 2 1.2 为什么学习统计学 2 1.3 什么是统计学 4 1.4 统计学的类型 6 1.5 变量的类型 8 1.6 测量尺度 9 1.7 伦理与统计 14 1.8 计算机应用 14 本章小结 16 习题 16 数据集习题 19 自测题答案 20 第2章 描述数据：频数表、频数分布和图形表示 21 2.1 引言 22 2.2 构造频数表 23 2.3 构造频数分布：定量数据 29 2.4 一个软件例子 34 2.5 相对频数分布 34 2.6 频数分布的图形表示 36 本章小结 46 习题 46 数据集习题 53 软件命令 54 自测题答案 55 第3章 描述数据：数值度量 57 3.1 引言 58 3.2 总体均值 58 3.3 样本均值 60 3.4 算术平均数的性质 61 3.5 加权平均数 63 3.6 中位数 64 3.7 众数 65 3.8 软件解法 69 3.9 均值、中位数和众数的相对位置 69 3.10 几何平均数 72 3.11 为什么要研究离散程度 74 3.12 离散程度的度量 75 3.13 软件解法 84 3.14 标准差的解释与应用 85 3.15 分组数据的均值和标准差 88 3.16 伦理和结果报告 92 本章小结 92 符号读法 94 习题 94 数据集习题 99 软件命令 100 自测题答案 100 第4章 描述数据：数据展示和数据开发 102 4.1 引言 103 4.2 点状图 103 4.3 茎叶图 105 4.4 位置度量 111 4.5 偏度 119 4.6 描述两个变量之间的关系 124 本章小结 129 符号读法 129 习题 130 数据集习题 135 软件命令 135 自测题答案 136 第1~4章复习 137 术语 137 习题 139 案例 141 应用测试 142 第5章 概率论概述 144 5.1 引言 145 5.2 概率 146 5.3 分配概率方法 148 5.4 几种计算概率的法则 153 5.5 列联表 162 5.6 树形图 164 5.7 贝叶斯定理 167 5.8 计数原理 171 本章小结 176 符号读法 177 习题 178 数据集习题 182 软件命令 183 自测题答案 184 第6章 离散型概率分布 186 6.1 引言 187 6.2 概率分布 187 6.3 随机变量 189 6.4 概率分布的均值、方差和标准差 191 6.5 二项概率分布 195 6.6 超几何分布 204 6.7 泊松概率分布 207 本章小结 212 习题 213 数据集习题 218 软件命令 219 自测题答案 221 第7章 连续型概率分布 222 7.1 引言 223 7.2 均匀概率分布族 223 7.3 正态概率分布族 227 7.4 标准正态概率分布 229 7.5 二项分布的正态近似 242 7.6 指数分布族 246 本章小结 251 习题 252 数据集习题 256 软件命令 256 自测题答案 257 第5~7章复习 258 术语 259 问题 260 案例 261 应用测试 263 第8章 抽样方法和中心极限定理 265 8.1 引言 266 8.2 抽样方法 266 8.3 抽样误差 274 8.4 样本均值的抽样分布 275 8.5 中心极限定理 279 8.6 样本均值抽样分布的应用 286 本章小结 289 符号读法 290 习题 290 数据集习题 295 软件命令 295 自测题答案 296 第9章 估计和置信区间 297 9.1 引言 298 9.2 均值的点估计 298 9.3 总体均值的置信区间 299 9.4 比例的置信区间 313 9.5 选择适当的样本容量 316 9.6 有限总体修正因子 320 本章小结 323 习题 323 数据集习题 327 软件命令 328 自测题答案 329 第8～9章复习 329 术语 330 问题 331 案例 332 应用测试 332 第10章 单样本假设检验 333 10.1 引言 334 10.2 假设 334 10.3 假设检验 335 10.4 假设检验五步法 335 10.5 单侧与双侧显著性检验 340 10.6 总体均值的检验：已知总体标准差 341 10.7 假设检验中的p-值 345 10.8 总体均值的检验：总体标准差未知 348 10.9 关于比例的检验 356 10.10 第Ⅱ类错误 359 本章小结 362 符号读法 363 习题 364 数据集习题 368 软件命令 369 自测题答案 369 第11章 两样本假设检验 371 11.1 引言 372 11.2 两样本假设检验：独立样本 372 11.3 比例的两样本检验 378 11.4 总体均值的比较：总体标准差未知（合并t检验） 382 11.5 两样本的假设检验：相依样本 392 11.6 相依样本与独立样本的比较 395 本章小结 399 符号读法 400 习题 400 数据集习题 406 软件命令 407 自测题答案 408 第12章 方差分析 410 12.1 引言 411 12.2 F分布 411 12.3 比较两总体的方差 412 12.4 ANOVA的假定 416 12.5 ANOVA检验 418 12.6 关于成对处理均值的推断 426 12.7 双因素方差分析 430 12.8 具有交互作用的双因素方差分析 435 本章小结 442 符号读法 443 习题 443 数据集习题 451 软件命令 452 自测题答案 454 第10~12章复习 455 术语 455 习题 456 案例 459 应用测试 459 第13章 线性回归与相关 461 13.1 引言 462 13.2 相关分析 463 13.3 相关系数 465 13.4 相关系数的显著性检验 472 13.5 回归分析 476 13.6 斜率的显著性检验 483 13.7 评估回归方程的预测能力 486 13.8 预测区间估计 490 13.9 变换数据 495 本章小结 498 符号读法 499 习题 500 数据集习题 509 软件命令 510 自测题答案 511 第14章 多元回归与相关分析 512 14.1 引言 513 14.2 多元回归分析 513 14.3 评价多元回归方程 519 14.4 多元线性回归的推断 523 14.5 评价多元回归的假定 531 14.6 定性自变量 537 14.7 具有交互作用的回归模型 540 14.8 逐步回归 542 14.9 多元回归回顾 546 本章小结 551 符号读法 553 习题 553 数据集习题 565 软件命令 566 自测题答案 567 第13～14章复习 567 术语 568 问题 569 案例 570 应用测试 571 第15章 指数 573 15.1 引言 574 15.2 简单指数 574 15.3 为什么把数据转换成指数 577 15.4 指数的构造 577 15.5 未加权指数 579 15.6 加权指数 581 15.7 价值指数 585 15.8 特殊用途指数 587 15.9 消费价格指数 592 15.10 调整基期 595 本章小结 598 习题 599 软件命令 602 自测题答案 603 第16章 时间序列与预测 604 16.1 引言 605 16.2 时间序列的构成 605 16.3 移动平均 608 16.4 加权移动平均 611 16.5 线性趋势 615 16.6 最小二乘法 616 16.7 非线性趋势 618 16.8 季节波动 621 16.9 消除数据的季节影响 627 16.10 杜宾–沃森统计量 631 本章小结 636 习题 636 数据集习题 643 软件命令 643 自测题答案 644 第15～16章复习 645 术语 646 问题 646 应用测试 647 第17章 非参数方法：检验 648 17.1 引言 649 17.2 拟合优度检验：期望频数相等 649 17.3 拟合优度检验：期望频数不等 655 17.4 卡方的局限性 657 17.5 检验一组数据是否来自正态总体 659 17.6 正态检验的图形和统计方法 662 17.7 列联表分析 667 本章小结 672 符号读法 672 习题 672 数据集习题 677 软件命令 678 自测题答案 679 第18章 非参数方法：分级数据分析 680 18.1 引言 681 18.2 符号检验 681 18.3 相依样本的威尔科克森符号秩检验 690 18.4 独立样本的威尔科克森秩和检验 695 18.5 克鲁斯卡尔–沃利斯检验：秩方差分析 698 18.6 秩相关 704 本章小结 709 符号读法 710 习题 710 数据集习题 713 软件命令 713 自测题答案 714 第17～18章复习 716 术语 716 问题 717 案例 718 应用测试 718 第19章 统计过程控制与质量管理 720 19.1 引言 721 19.2 质量控制简史 721 19.3 差异产生的原因 724 19.4 诊断图 725 19.5 质量控制图的用途和类型 729 19.6 受控和失控情形 734 19.7 属性控制图 737 19.8 验收抽样 742 本章小结 746 符号读法 747 习题 747 软件命令 751 自测题答案 Contents Chapter What Is Statistics? 1 1.1 Introduction 2 1.2 Why Study Statistics? 2 1.3 What Is Meant by Statistics? 4 1.4 Types of Statistics 6 1.5 Types of Variables 8 1.6 Levels of Measurement 9 Descriptive Statistics 6 Inferential Statistics 6 Nominal-Level Data 10 Ordinal-Level Data 11 Interval-Level Data 11 Ratio-Level Data 12 Exercises 14 1.7 Ethics and Statistics 14 1.8 Computer Applications 14 Chapter Summary 16 Chapter Exercises 16 Data Set Exercises 19 Answers to Self-Review 20 Chapter 2Describing Data: Frequency Tables, Frequency Distributions, and GraphicPresentation 21 2.1 Introduction 22 2.2 Constructing a Frequency Table 23 Relative Class Frequencies 23 Graphic Presentation of Qualitative Data 24 Exercises 28 2.3 Constructing Frequency Distributions:Quantitative Data 29 2.4 A Software Example 34 2.5 Relative Frequency Distribution 34 Exercises 35 2.6 Graphic Presentation of a Frequency Distribution 36 Histogram 36 Frequency Polygon 38 Exercises 41 Cumulative Frequency Distributions 42 Exercises 44 Chapter Summary 46 Chapter Exercises 46 Data Set Exercises 53 Software Commands 54 Answers to Self-Review 55 Chapter 3 Describing Data: Numerical Measures 57 3.1 Introduction 58 3.2 The Population Mean 58 3.3 The Sample Mean 60 3.4 Properties of the Arithmetic Mean 61 Exercises 62 3.5 The Weighted Mean 63 Exercises 64 3.6 The Median 64 3.7 The Mode 65 Exercises 67 3.8 Software Solution 69 3.9 The Relative Positions of the Mean, Median, and Mode 69 Exercises 71 3.10 The Geometric Mean 72 Exercises 73 3.11 Why Study Dispersion? 74 3.12 Measures of Dispersion 75 Range 75 Mean Deviation 76 Exercises 79 Variance and Standard Deviation 79 Exercises 82 3.13 Software Solution 84 Exercises 84 3.14 Interpretation and Uses of the Standard Deviation 85 Chebyshev’s Theorem 85 The Empirical Rule 86 Exercises 87 3.15 The Mean and Standard Deviation of Grouped Data 88 The Arithmetic Mean 88 Standard Deviation 89 Exercises 91 3.16 Ethics and Reporting Results 92 Chapter Summary 92 Pronunciation Key 94 Chapter Exercises 94 Data Set Exercises 99 Software Commands 100 Answers to Self-Review 100 Chapter 4 Describing Data: Displaying and Exploring Data 102 4.1 Introduction 103 4.2 Dot Plots 103 4.3 Stem-and-Leaf Displays 105 Exercises 109 4.4 Measures of Position 111 Quartiles, Deciles, and Percentiles 111 Exercises 115 Box Plots 116 Exercises 118 4.5 Skewness 119 Exercises 123 4.6 Describing the Relationship between TwoVariables 124 Exercises 127 Chapter Summary 129 Pronunciation Key 129 Chapter Exercises 130 Data Set Exercises 135 Software Commands 135 Answers to Self-Review 136 A Review of Chapters 1–4 137 Glossary 137 Problems 139 Cases 141 Practice Test 142 Chapter 5 A Survey of Probability Concepts 144 5.1 Introduction 145 5.2 What Is a Probability? 146 5.3 Approaches to Assigning Probabilities 148 Classical Probability 148 Empirical Probability 149 Subjective Probability 150 Exercises 152 5.4 Some Rules for Computing Probabilities 153 Rules of Addition 153 Exercises 158 Rules of Multiplication 159 5.5 Contingency Tables 162 5.6 Tree Diagrams 164 Exercises 166 5.7 Bayes’ Theorem 167 Exercises 170 5.8 Principles of Counting 171 The Multiplication Formula 171 The Permutation Formula 172 The Combination Formula 174 Exercises 176 Chapter Summary 176 Pronunciation Key 177 Chapter Exercises 178 Data Set Exercises 182 Software Commands 183 Answers to Self-Review 184 Chapter 6 Discrete Probability Distributions 186 6.1 Introduction 187 6.2 What Is a Probability Distribution? 187 6.3 Random Variables 189 Discrete Random Variable 190 Continuous Random Variable 190 6.4 The Mean, Variance, and Standard Deviation of a Discrete Probability Distribution 191 Mean 191 Variance and Standard Deviation 191 Exercises 193 6.5 Binomial Probability Distribution 195 How Is a Binomial Probability Computed?196 Binomial Probability Tables198 Exercises201 Cumulative Binomial Probability Distributions202 Exercises203 6.6 Hypergeometric Probability Distribution204 Exercises207 6.7 Poisson Probability Distribution207 Exercises212 Chapter Summary212 Chapter Exercises213 Data Set Exercises218 Software Commands219 Answers to Self-Review221 Chapter 7 Continuous Probability Distributions 222 7.1 Introduction223 7.2 The Family of Uniform ProbabilityDistributions 223 Exercises 226 7.3 The Family of Normal ProbabilityDistributions 227 7.4 The Standard Normal ProbabilityDistribution 229 Applications of the Standard NormalDistribution 231 The Empirical Rule 231 Exercises 233 Finding Areas under the Normal Curve 233 Exercises 236 Exercises 239 Exercises 241 7.5 The Normal Approximation to the Binomial 242 Continuity Correction Factor 242 How to Ap the Correction Factor 244 Exercises 245 7.6 The Family of Exponential Distributions 246 Exercises 250 Chapter Summary 251 Chapter Exercises 252 Data Set Exercises 256Software Commands 256 Answers to Self-Review 257 A Review of Chapters 5–7 258 Exercises 203 Glossary 259 Problems 260 Cases 261 Practice Test 263 Chapter 8 Sampling Methods and the Central Limit Theorem 265 8.1 Introduction 266 8.2 Sampling Methods 266 Reasons to Sample 266 Simple Random Sampling 267 Systematic Random Sampling 270 Exercises272 8.3 Sampling “Error”274 8.4 Sampling Distribution of the Sample Mean275 Exercises278 8.5 The Central Limit Theorem279 Exercises285 8.6 Using the Sampling Distribution of theSample Mean286 Exercises289 Chapter Summary289 Pronunciation Key290 Chapter Exercises290 Data Set Exercises295 Software Commands295 Answers to Self-Review296 Chapter 9 Estimation and ConfidenceIntervals297 9.1 Introduction298 9.2 Point Estimate for a Population Mean298 9.3 Confidence Intervals for a PopulationMean299 Population Standard Deviation Known 300 A Computer Simulation304 Exercises305 Population Standard Deviation Unknown306 Exercises 312 9.4 A Confidence Interval for a Proportion 313 Exercises 316 9.5 Choosing an Appropriate Sample Size 316 Sample Size to Estimate a Population Mean 317 Sample Size to Estimate a PopulationProportion 318 Exercises 320 9.6 Finite-Population Correction Factor 320 Exercises 322 Chapter Summary 323 Chapter Exercises 323 Data Set Exercises 327 Software Commands 328 Answers to Self-Review 329 A Review of Chapters 8 and 9 329 Glossary 330 Problems 331 Case 332 Practice Test 332 10.4 Five-Step Procedure for Testing aHypothesis 335 Step 1: State the Null Hypothesis (H0) and theAlternate Hypothesis (H1)336 Step 2: Select a Level of Significance337 Step 3: Select the Test Statistic338 Step 4: Formulate the Decision Rule338 Step 5: Make a Decision339 10.5 One-Tailed and Two-Tailed Tests ofSignificance340 10.6 Testing for a Population Mean: KnownPopulation Standard Deviation341 A Two-Tailed Test341 A One-Tailed Test345 10.7 p-Value in Hypothesis Testing345 Exercises347 10.8 Testing for a Population Mean: Population Standard Deviation Unknown348 Exercises352 A Software Solution 353 Exercises 355 10.9 Tests Concerning Proportions 356 Exercises 359 10.10 Type II Error 359 Exercises 362 Chapter Summary 362 Pronunciation Key 363 Chapter Exercises 364 Data Set Exercises 368 Software Commands 369 Answers to Self-Review 369 Chapter11 Two-Sample Tests of Hypothesis 371 11.1 Introduction372 11.2 Two-Sample Tests of Hypothesis:Independent Samples372 Exercises377 11.3 Two-Sample Tests about Proportions378 Exercises381 11.4 Comparing Population MeanswithUnknown Population Standard Deviations382 Equal Population Standard Deviations383 Exercises386 Unequal Population Standard Deviations388 Exercises391 11.5 Two-Sample Tests of Hypothesis:Dependent Samples392 11.6 Comparing Dependent and Independent Samples 395 Exercises398 Chapter Summary399 Pronunciation Key 400 Chapter Exercises 400 Data Set Exercises 406 Software Commands 407 Answers to Self-Review 408 Chapter12 Analysis of Variance410 12.1 Introduction411 12.2 The FDistribution411 12.3 Comparing Two Population Variances412 Exercises415 12.4 ANOVA Assumptions416 12.5 The ANOVA Test418 Exercises425 12.6 Inferences about Pairs of TreatmentMeans426 Exercises429 12.7 Two-Way Analysis of Variance430 Exercises434 12.8 Two-Way ANOVA with Interaction435 Interaction Plots 436 Hypothesis Test for Interaction 437 Exercises 440 Chapter Summary 442 Pronunciation Key 443 Chapter Exercises 443 Data Set Exercises 451 Software Commands 452 Answers to Self-Review 454 A Review of Chapters 10–12455 Glossary 455 Problems 456 Cases 459 Practice Test 459 Chapter13Correlation and Linear Regression 461 13.1 Introduction 462 13.2 What Is Correlation Analysis? 463 13.3 The Correlation Coefficient 465 Exercises 470 13.4 Testing the Significance of the Correlation Coefficient 472 Exercises475 13.5 Regression Analysis 476 Least Squares Principle 476 Drawing the Regression Line 479 Exercises481 13.6 Testing the Significance of the Slope483 Exercises486 13.7 Evaluating a Regression Equation’s Abilityto Predict486 The Standard Error of Estimate486 The Coefficient of Determination487 Exercises488 Relationships among the CorrelationCoefficient, the Coefficient of Determination,and the Standard Error of Estimate 488 Exercises490 13.8 Interval Estimates of Prediction 490 Assumptions Underlying Linear Regression 490 Constructing Confidence and Prediction Intervals 492 Exercises 494 13.9 Transforming Data495 Exercises 497 Chapter Summary 498 Pronunciation Key 499 Chapter Exercises500 Data Set Exercises509 Software Commands510 Answers to Self-Review 511 Chapter 14 Multiple Regression Analysis512 14.1 Introduction5131 4.2 Multiple Regression Analysis513 Exercises517 14.3 Evaluating a Multiple RegressionEquation 519 The ANOVA Table519Multiple Standard Error of Estimate520 Coefficient of Multiple Determination521 Adjusted Coefficient of Determination522 Exercises523 14.4 Inferences in Multiple Linear Regression523 Global Test: Testing the Multiple RegressionModel524 Evaluating Individual Regression Coefficients526 Exercises530 14.5 Evaluating the Assumptions of MultipleRegression531 Linear Relationship532 Variation in Residuals Same for Large and Small Values533 Distribution of Residuals534 Multicollinearity534 Independent Observations537 14.6 Qualitative Independent Variables537 14.7 Regression Models with Interaction540 14.8 Stepwise Regression542 Exercises544 14.9 Review of Multiple Regression546 Chapter Summary551 Pronunciation Key553 Chapter Exercises553 Data Set Exercises565 Software Commands566 Answers to Self-Review567 A Review of Chapters 13 and 14 567 Glossary568 Problems569 Cases570 Practice Test571 Chapter 15 Index Numbers573 15.1 Introduction574 15.2 Simple Index Numbers574 15.3 Why Convert Data to Indexes?577 15.4 Construction of Index Numbers577 Exercises578 15.5 Unweighted Indexes579 Simple Average of the Price Indexes579 Simple Aggregate Index580 15.6 Weighted Indexes581 Laspeyres Price Index581Paasche Price Index582 Fisher’s Ideal Index584 Exercises584 15.7 Value Index 585 Exercises586 15.8 Special-Purpose Indexes587 Consumer Price Index588 Producer Price Index589 Dow Jones Industrial Average (DJIA)589S&P 500 Index590 Exercises591 15.9 Consumer Price Index592 Special Uses of the Consumer Price Index592 15.10 Shifting the Base595 Exercises597 Chapter Summary598 Chapter Exercises599 Software Commands602 Answers to Self-Review603 Chapter16Time Series and Forecasting604 16.1 Introduction605 16.2 Components of a Time Series605 Secular Trend605 Cyclical Variation606 Seasonal Variation607 Irregular Variation608 16.3 A Moving Average608 16.4 Weighted Moving Average611 Exercises614 16.5 Linear Trend615 16.6 Least Squares Method616 Exercises618 16.7 Nonlinear Trends618 Exercises620 16.8 Seasonal Variation621 Determining a Seasonal Index621 Exercises626 16.9 Deseasonalizing Data627 Using Deseasonalized Data to Forecast628 Exercises630 16.10 The Durbin-Watson Statistic631 Exercises636 Chapter Summary636 Chapter Exercises636 Data Set Exercise643 Software Commands643 Answers to Self-Review644 A Review of Chapters 15 and 16 645 Glossary646 Problems646 Practice Test647 Chapter 17 Nonparametric Methods:Goodness-of-Fit Tests 648 17.1 Introduction649 17.2 Goodness-of-Fit Test: Equal ExpectedFrequencies 649 Exercises654 17.3 Goodness-of-Fit Test: Unequal ExpectedFrequencies 655 17.4 Limitations of Chi-Square657 Exercises659 17.5 Testing the Hypothesis That a Distribution of Data Is from a Normal Population 659 17.6 Graphical and Statistical ApproachestoConfirm Normality662 Exercises665 17.7 Contingency Table Analysis667 Exercises671 Chapter Summary672 Pronunciation Key672 Chapter Exercises672 Data Set Exercises677 Software Commands678 Answers to Self-Review679 Chapter 18 Nonparametric Methods: Analysis of Ranked Data680 18.1 Introduction681 18.2 The Sign Test681 Exercises685 Using the Normal Approximation to theBinomial686 Exercises688 Testing a Hypothesis about a Median688 Exercises689 18.3 Wilcoxon Signed-Rank Test forDependent Samples690 Exercises693 18.4 Wilcoxon Rank-Sum Test for IndependentSamples695 Exercises698 18.5 Kruskal-Wallis Test: Analysis of Varianceby Ranks698 Exercises702 18.6 Rank-Order Correlation704 Testing the Significance of rs706 Exercises707 Chapter Summary709 Pronunciation Key710 Chapter Exercises710 Data Set Exercises713 Software Commands713 Answers to Self-Review714 A Review of Chapters 17 and 18 716 Glossary716 Problems717 Cases718 Practice Test718 Chapter 19 Statistical Process Control andQuality Management720 19.1 Introduction721 19.2 A Brief History of Quality Control 721 Six Sigma724 19.3 Causes of Variation724 19.4 Diagnostic Charts725 Pareto Charts725 Fishbone Diagrams727 Exercises728 19.5 Purpose and Types of Quality ControlCharts729 Control Charts for Variables729 Range Charts733 19.6 In-Control and Out-of-Control Situations734 Exercises736 19.7 Attribute Control Charts737 Percent Defective Charts737 c-Bar Charts740 Exercises741 19.8 Acceptance Sampling742 Exercises746 Chapter Summary746 Pronunciation Key747 Chapter Exercises747 Appendixes AppendixA:Data Sets AppendixB:Tables AppendixC:Answers |
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