商務(wù)統計：決策與分析（英文版）（附光盤(pán)）簡(jiǎn)介，目錄書(shū)摘
2020-05-26 19:11
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作者：京東
商務(wù)統計：決策與分析（英文版）（附光盤(pán)）
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編輯推薦: 《商務(wù)統計：決策與分析（英文版）》啟發(fā)性案例：每章都從一個(gè)商業(yè)案例開(kāi)始，提出問(wèn)題并引出該章內容。4M示例：4M（動(dòng)機、方法、實(shí)施、結論）的問(wèn)題解決策略為學(xué)生解決商務(wù)問(wèn)題提供了清晰的思路。每個(gè)4M示例都先提出一個(gè)商業(yè)問(wèn)題，然后引導學(xué)生尋求解決該問(wèn)題的最佳統計方法，使用統計軟件實(shí)現，并說(shuō)明分析結果。
陷阱：為避免發(fā)生常見(jiàn)錯誤，每章結尾處給出一些有用的提示。
軟件提示：每章都有關(guān)于運用Excel（2003和2007）、Minitab和JMP進(jìn)行計算的提示。
背后的數學(xué)：在多數章節的最后，提供了一些有趣的技術(shù)細節，以解釋某些重要結論，如對某個(gè)基本公式的證明或解釋。
實(shí)際的統計案例研究：每部分最后都包括兩個(gè)深度案例研究，這些案例使用真實(shí)數據，涉及股票價(jià)格、經(jīng)理人薪酬、企業(yè)債券違約、零售額管理和過(guò)程控制等方面。
隨書(shū)光盤(pán)中包括純文本、Excel、Minitab 14、Minitab 15和SPSS（PASW）格式的數據集文件以及Excel的一個(gè)統計學(xué)插件DDXL。
陷阱：為避免發(fā)生常見(jiàn)錯誤，每章結尾處給出一些有用的提示。
軟件提示：每章都有關(guān)于運用Excel（2003和2007）、Minitab和JMP進(jìn)行計算的提示。
背后的數學(xué)：在多數章節的最后，提供了一些有趣的技術(shù)細節，以解釋某些重要結論，如對某個(gè)基本公式的證明或解釋。
實(shí)際的統計案例研究：每部分最后都包括兩個(gè)深度案例研究，這些案例使用真實(shí)數據，涉及股票價(jià)格、經(jīng)理人薪酬、企業(yè)債券違約、零售額管理和過(guò)程控制等方面。
隨書(shū)光盤(pán)中包括純文本、Excel、Minitab 14、Minitab 15和SPSS（PASW）格式的數據集文件以及Excel的一個(gè)統計學(xué)插件DDXL。
內容簡(jiǎn)介: 現在商業(yè)競爭日益激烈，有效做出商務(wù)決策變得至關(guān)重要。本書(shū)從實(shí)際的商業(yè)問(wèn)題出發(fā)，詳細闡述如何利用數據進(jìn)行信息決策，并將統計概念與實(shí)際問(wèn)題聯(lián)系起來(lái)，告訴讀者如何尋找模式從數據建立統計模型，以及如何提供調查結果。書(shū)中涵蓋了應用統計學(xué)在當代商務(wù)經(jīng)濟領(lǐng)域中幾乎所有的重要應用，并且統計軟件（包括Excel、Minitab等）的使用貫穿全書(shū)。
作者簡(jiǎn)介: Robert Stine 于普林斯頓大學(xué)獲得博士學(xué)位。自1983年以來(lái)他一直在賓夕法尼亞大學(xué)沃頓商學(xué)院講授商務(wù)統計學(xué)課程。在任教期間，他獲得了多項教學(xué)獎，包括MBA核心教學(xué)獎、David W. Hauck優(yōu)秀教學(xué)獎。他的研究領(lǐng)域包括計算機軟件、時(shí)間序列分析和預測、與模型識別和選擇相關(guān)的一般問(wèn)題等。
Dean Foster 于馬里蘭大學(xué)獲得博士學(xué)位。他曾在芝加哥大學(xué)任教，自1992年以來(lái)任教于賓夕法尼亞大學(xué)沃頓商學(xué)院。他講授的課程有商務(wù)統計初步、概率論與馬爾可夫鏈、統計計算和高等統計學(xué)等。其研究領(lǐng)域包括隨機過(guò)程的統計推斷、博弈論、機器學(xué)習和變量選擇。
Dean Foster 于馬里蘭大學(xué)獲得博士學(xué)位。他曾在芝加哥大學(xué)任教，自1992年以來(lái)任教于賓夕法尼亞大學(xué)沃頓商學(xué)院。他講授的課程有商務(wù)統計初步、概率論與馬爾可夫鏈、統計計算和高等統計學(xué)等。其研究領(lǐng)域包括隨機過(guò)程的統計推斷、博弈論、機器學(xué)習和變量選擇。
目錄: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
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
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