Statistics for business:decision making and analysis

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作   者:(美)Robert A. Stine,(美)Dean P. Foster著

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ISBN:9787111342007

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简介

  现在商业竞争日益激烈,有效做出商务决策变得至关重要。本书从实际的商业问题出发,详细阐述如何利用数据进行信息决策,并将统计概念与实际问题联系起来,告诉读者如何寻找模式从数据建立统计模型,以及如何提供调查结果。书中涵盖了应用统计学在当代商务经济领域中几乎所有的重要应用,并且统计软件(包括Excel、Minitab等)的使用贯穿全书。   本书特色   ? 启发性案例:每章都从一个商业案例开始,提出问题并引出该章内容。   ? 4M示例:4M(动机、方法、实施、结论)的问题解决策略为学生解决商务问题提供了清晰的思路。每个4M示例都先提出一个商业问题,然后引导学生寻求解决该问题的最佳统计方法,使用统计软件实现,并说明分析结果。   ? 陷阱:为避免发生常见错误,每章结尾处给出一些有用的提示。   ? 软件提示:每章都有关于运用Excel(2003和2007)、Minitab和JMP进行计算的提示。   ? 背后的数学:在多数章节的最后,提供了一些有趣的技术细节,以解释某些重要结论,如对某个基本公式的证明或解释。   ? 实际的统计案例研究:每部分最后都包括两个深度案例研究,这些案例使用真实数据,涉及股票价格、经理人薪酬、企业债券违约、零售额管理和过程控制等方面。   随书光盘中包括纯文本、Excel、Minitab 14、Minitab 15和SPSS(PASW)格式的数据集文件以及Excel的一个统计学插件DDXL。  

目录

  Preface iii
  Index of Applications xvii
  PART ONEVariation
  1Introduction2
  1.1What is Statistics?2
  1.2Previews4
  1.3How to Use This Book92Data13
  2.1Data Tables14
  2.2Categorical and Numerical Data15
  2.3Recoding and Aggregation17
  2.4Time Series20
  2.5Further Attributes of Data21
  Chapter Summary24
  3Describing Categorical Data28
  3.1Looking at Data29
  3.2Charts of Categorical Data31
  3.3The Area Principle35
  3.4Mode and Median40
  Chapter Summary43
  4Describing Numerical Data52
  4.1Summaries of Numerical Variables53
  4.2Histograms and the Distribution of Numerical Data57
  4.3Boxplot60
  4.4Shape of a Distribution62
  4.5Epilog66
  Chapter Summary69
  5Association between Categorical Variables77
  5.1Contingency Tables78
  5.2Lurking Variables and Simpson’s Paradox85
  5.3Strength of Association89
  Chapter Summary95
  6Association between Quantitative Variables104
  6.1Scatterplots105
  6.2Association in Scatterplots107
  6.3Measuring Association109
  6.4Summarizing Association with a Line115
  6.5Spurious Correlation118
  Chapter Summary123
  STATISTICS IN ACTION CASEFinancial time series134
  STATISTICS IN ACTION CASEExecutive compensation142
  PARTTWO Probability
  7Probability150
  7.1From Data to Probability151
  7.2Rules for Probability156
  7.3Independent Events161
  Chapter Summary165
  8Conditional Probability174
  8.1From Tables to Probabilities175
  8.2Dependent Events178
  8.3Organizing Probabilities182
  8.4Order in Conditional Probabilities185
  Chapter Summary190
  9Random Variables196
  9.1Random Variables197
  9.2Properties of Random Variables200
  9.3Properties of Expected Values205
  9.4Comparing Random Variables207
  Chapter Summary209
  10Association between Random Variables218
  10.1Portfolios and Random Variables219
  10.2Joint Probability Distribution221
  10.3Sums of Random Variables224
  10.4Dependence between Random Variables225
  10.5IID Random Variables230
  10.6Weighted Sums232
  Chapter Summary236
  11Probability Models for Counts243
  11.1Random Variables for Counts244
  11.2Binomial Model246
  11.3Properties of Binomial Random Variables247
  11.4Poisson Model251
  Chapter Summary257
  12The Normal Probability Model261
  12.1Normal Random Variable262
  12.2The Normal Model265
  12.3Percentiles271
  12.4Departures from Normality272
  Chapter Summary278
  STATISTICS IN ACTION CASEManaging Financial Risk287
  STATISTICS IN ACTION CASEModeling Sampling Variation296
  PART THREE Inference
  13Samples and Surveys304
  13.1Two Surprising Properties of Sampling305
  13.2Variation310
  13.3Alternative Sampling Methods314
  13.4Checklist for Surveys317
  Chapter Summary321
  14Sampling Variation and Quality325
  14.1Sampling Distribution of the Mean326
  14.2Control Limits331
  14.3Using a Control Chart334
  14.4Control Charts for Variation337
  Chapter Summary343
  15Confidence Intervals351
  15.1Ranges for Parameters352
  15.2Confidence Interval for the Mean357
  15.3Interpreting Confidence Intervals360
  15.4Manipulating Confidence Intervals362
  15.5Margin of Error364
  Chapter Summary371
  16Statistical Tests378
  16.1Concepts of Statistical Tests379
  16.2Testing the Proportion384
  16.3Testing the Mean388
  16.4Other Properties of Tests393
  Chapter Summary397
  17Alternative Approaches to Inference403
  17.1A Confidence Interval for the Median404
  17.2Transformations410
  17.3Prediction Intervals411
  17.4Proportions Based on Small Samples415
  Chapter Summary419
  18Comparison424
  18.1Data for Comparisons425
  18.2Two-sample t-test427
  18.3Confidence Interval for the Difference432
  18.4Other Comparisons435
  Chapter Summary444
  STATISTICS IN ACTION CASERare Events450
  STATISTICS IN ACTION CASETesting Association456
  PART FOUR Regression Models
  19Linear Patterns464
  19.1Fitting a Line to Data465
  19.2Interpreting the Fitted Line467
  19.3Properties of Residuals472
  19.4Explaining Variation474
  19.5Conditions for Simple Regression475
  Chapter Summary481
  20Curved Patterns488
  20.1Detecting Nonlinear Patterns489
  20.2Transformations491
  20.3Reciprocal Transformation492
  20.4Logarithm Transformation497
  Chapter Summary506
  21The Simple Regression Model513
  21.1The Simple Regression Model514
  21.2Conditions for the Simple Regression Model518
  21.3Inference in Regression521
  21.4Prediction Intervals529
  Chapter Summary537
  22Regression Diagnostics545
  22.1Problem 1:Changing Variation546
  22.2Problem 2: Leveraged Outliers555
  22.3Problem 3:Dependent Errors and Time Series559
  Chapter Summary566
  23Multiple Regression573
  23.1The Multiple Regression Model574
  23.2Interpreting Multiple Regression575
  23.3Checking Conditions581
  23.4Inference in Multiple Regression584
  23.5Steps in Fitting a Multiple Regression588
  Chapter Summary594
  24Building Regression Models605
  24.1Identifying Explanatory Variables606
  24.2Collinearity611
  24.3Removing Explanatory Variables616
  Chapter Summary627
  25Categorical Explanatory Variables635
  25.1Two-sample Comparisons636
  25.2Analysis of Covariance639
  25.3Checking Conditions642
  25.4Interactions and Inference644
  25.5Regression with Several Groups651
  Chapter Summary656
  26Analysis of Variance665
  26.1Comparing Several Groups666
  26.2Inference in Anova Regression Models673
  26.3Multiple Comparisons677
  26.4Groups of Different Size680
  Chapter Summary686
  27Time Series694
  27.1Decomposing a Time Series695
  27.2Regression Models698
  27.3Checking the Model708
  Chapter Summary719
  STATISTICS IN ACTION CASEAnalyzing Experiments728
  STATISTICS IN ACTION CASEAutomated Modeling736
  Appendix: Tables743
  AnswersA-1
  Photo AcknowledgmentsC-1
  IndexI-1
  

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