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商务与经济统计：英文版·第6版
作者：（美）戴维·R.安德森（David R.Anderson）等著
出版社：机械工业出版社
出版时间：1998-07-01
ISBN：9787111065975
定价：¥102.00
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内容简介
统计，是处理现代社会经济问题时不可缺少的重要工具之一。本书就是针对那些从事企业管理和置身于经济领域的人士而写，向他们介绍统计学的基本概念，理论，并着重讲解如何把统计学应用在管理和经济工作中。为了使读者学会使用统计学方法，作者从《华尔街时报》、《商业周刊》、《今日美国》、《财富》、《福布斯》、《金融世界》等处摘引大量的真实的数据和案例，进行了分析讲解，并与书中的各种统计方法一一对应。案例中不乏中国读者耳熟能详的企业，如高露洁公司，施乐公司，宝洁公司以及道尔化学公司等。案例的分析贯穿全书始终，而且，各部分均附有自测题，参考答案集中在本书的附录部分，便于读者检验自己的水平。本书着重于统计在实际工作中的应用，并详尽介绍了统计方法的演变过程，可作为一步研究高级统计理论的入门教程。
作者简介
暂缺《商务与经济统计：英文版·第6版》作者简介
目录
Chapter 1
DATA AND STATISTICS1.1
applications in Business and Economics1.2
Data 51.3
Data Sources 71.4
Descriptive Statistics1.5
Statistical Inference and ProbabilityChapter 2
DESCRIPTIVE STATISTICS I:
TABULAR AND GRAPHICAL METHODS2.1
Summarizing Qualitative Data2.2
Summarizing Quantitative Data2.3
The Role of the computer2.4
Exploratory Data analysis2.5
Crosstabulations and Scatter diagramsChapter 3
DESCRIPTIVE STATISTICS II: NUMERICAL METHODS3.1
Measures of Location3.2
Measures of Dispersion3.3
Some Uses of the Mean and the Standard Deviation3.4
Exploratory Data Analysis3.5
Measures of association Beteen Two Variables3.6
The Role of the computer3.7
Computing Measures of Location and dispersion for Grouped dataChapter 4
INTRODUCTION TO PROBABILITY4.1
Experiments, the Sample space, and counting rules4.2
Assigning Probabilities to Experimental Outcomes4.3
Events and Their Probabilities4.4
some Basic Relationships of Probability4.5
Conditional Probability4.6
Bayes''TheoremChapter 5
DISCRETE PROBABILITY DISTRIBUTIONS5.1
Random Variables5.2
Discrete Probability Distributions5.3
Expected Value and Varince5.4
the Binomial Probability Distribution5.5
The Poisson Probability distribution5.6
The Hypergeometric Probability DistributionChapter 6
CONTINUOUS PROBABILITY DISTRIBUTIONS6.1
the Uniform Probability Distribution6.2
The Normal Probability Distribution6.3
Normal approximation of Binomial Probabilities6.4
The Exponential Probability DistributionChapter 7
SAMPLING AND SAMPLING DISTRIBUTIONS7.1
The Electronics Associates Sampling Problem7.2
Simple Random Sampling7.3
Point Estimation7.4
Introduction to Sampling distributions7.5
Sampling distribution of 7.6
Sampling distribution of 7.7
Properties of Point Estimators7.8
Other Sampling MethodsChapter 8
INTERVAL ESTIMATION8.1
Interval Estimation of a Population Mean: Large-Sample Case8.2
Interval Estimation of a Population Mean: small-Sample Case8.3
Determining the Sample size8.4
Interval Estimation of a Population ProportionChapter 9
HYPOTHESIS TESTING9.1
Developing Null and Alternative Hypotheses9.2
Type I and Type II Errors9.3
One-Tailed Tests About a Population Mean: Large-Sample Case9.4
Two-Tailed Tests About a Population Mean: Large-Sample Case9.5
Tests about a Population Mean: small-Sample Case9.6
Tests about a Popultion Proportion9.7
Hypothesis Testing and DecisionMaking9.8
Calculating the Probability of Type II Errors9.9
Determining the Sample size for a Hypothesis Test About a PopulationChapter 10 STATISTICAL INFERENCE
ABOUT MEANS AND PROPORTIONS WITH TWO POPULATIONS10.1
Estimation of the Difference between the Means of Two Populations: Independent Samples10.2
Hypothesis Tests about the Difference between the
Means of Two Populations: Independent Samples10.3
Inferences about the Difference between the Means of Two Populations: Matched Samples10.4
Inferences about the difference between the Proportions of Two PopulationsChapter 11
INFERENCES ABOUT POPULATION VARIANCES11.1
Inferences about a Population Variance11.2
Inferences about the Variances of Two PopulationsChapter 12
TESTS OF GOODNESS OF FIT AND INDEPENDENCE12.1
Goodness of fit Test: A Multinomial Ppulation12.2
Test of Independence: contingency Tables12.3
Goodness of fit Test: Poisson and Normal distributionsChapter 13
ANALYSIS OF VARIANCE AND EXPERIMENTAL DESIGN13.1
An Introduction to analysis of Variance13.2 Analysis of Variance: Testing for the Equality of k Population Means13.3
Multiple comparison Procedures13.4
An Introduction to Experimental Design13.5
completely Randomized Designs13.6
Randomized Block Design13.7
Factoril ExperimentsChapter 14
SIMPLE LINEAR REGRESSION14.1
The Simple Linear Regression Model14.2
The Least Squares Method14.3
The coefficient of Determination14.4
Model Assumptions14.5
Testing for Significance14.6
Using the Estimated Regression Equation for Estimation and Prediction 14.7
Computer Solution of Regression Problems14.8
Residual Analysis: Testing Model Assumptions14.9
Residual analysis: Outliers and Influential ObservationsChapter 15
MULTIPLE REGRESSION15.1
The Multiple Regression Model15.2
The Least Squares Method15.3
The Multiple Coefficient of Determination15.4
Model Assumptions15.5
Testing for significance15.6
Using the Estimated Regression Equation for Estimation and Prediction 15.7
qualitative Indepedent Variables15.8
Residul anlysisChapter 16
REGRESSION ANALYSIS: MODEL BUILDING16.1
The General Linear Model16.2
Determining when to Add or Delete Variables16.3
First Steps in the analysis of a Larger Problem16.4
Variable-Selection Procedures16.5
Residual Analysis16.6
Multiple Regression approach to Analysis of Variance and Experimental DesignChapter 17
INDEX NUMBERS17.1
Price Relatives17.2
aggregate Price Indexes17.3
computing an Aggregate Index from Price Relatives17.4
Some Important Price Indexes17.5
Deflating a Series by Price Indexes17.6
Price Indexes: Other considerations17.7
quantity IndexesChapter 18
FORECASTING18.1
The Components of a Time Series18.2
Using smoothing Methods in forecasting18.3
Using Trend Projection in forecasting18.4
Using Trend and Seasonal components in Forecasting18.5
Using Regression Analysis in Forecasting18.6
Qualitative Approches to ForecastingChapter 19
NONPARAMETRIC METHODS19.1
sign Text19.2
Wilcoxon Signed-rnk Test19.3
Mann-Whitney-Wilcoxon Test19.4
Kruskal-Wallis Test19.5
Rank CorrelationChapter 20
STATISTICAL METHODS FOR QUALITY CONTROL20.1
Statistical Process Control20.2
Acceptance amplingChapter 21
SAMPLE SURVEY21.1
Terminology Used in Sample Surveys21.2
Types of Surveys and Sampling Methods21.3
Survey Errors21.4
simple Random Sampling21.5
Stratified simple Random Sampling21.6
cluster Sampling 21.7
Systematic samplingChapter 22
DECISION ANALYSIS22.1
Structuring the Decision Problem22.2
Decision Making with Probabilities22.3
Expected Value of Perfect Information22.4
Decision Analysis With Sample Information22.5
Developing a Decision strategy''22.6
Expected Value of Sample InformationAppendixesA. Reference and BiliographyB. TablesC. summtion NotationD. the Data DiskE. Answers to Even-Numbered ExercisesF. solutions to Self-Test Exercises
DATA AND STATISTICS1.1
applications in Business and Economics1.2
Data 51.3
Data Sources 71.4
Descriptive Statistics1.5
Statistical Inference and ProbabilityChapter 2
DESCRIPTIVE STATISTICS I:
TABULAR AND GRAPHICAL METHODS2.1
Summarizing Qualitative Data2.2
Summarizing Quantitative Data2.3
The Role of the computer2.4
Exploratory Data analysis2.5
Crosstabulations and Scatter diagramsChapter 3
DESCRIPTIVE STATISTICS II: NUMERICAL METHODS3.1
Measures of Location3.2
Measures of Dispersion3.3
Some Uses of the Mean and the Standard Deviation3.4
Exploratory Data Analysis3.5
Measures of association Beteen Two Variables3.6
The Role of the computer3.7
Computing Measures of Location and dispersion for Grouped dataChapter 4
INTRODUCTION TO PROBABILITY4.1
Experiments, the Sample space, and counting rules4.2
Assigning Probabilities to Experimental Outcomes4.3
Events and Their Probabilities4.4
some Basic Relationships of Probability4.5
Conditional Probability4.6
Bayes''TheoremChapter 5
DISCRETE PROBABILITY DISTRIBUTIONS5.1
Random Variables5.2
Discrete Probability Distributions5.3
Expected Value and Varince5.4
the Binomial Probability Distribution5.5
The Poisson Probability distribution5.6
The Hypergeometric Probability DistributionChapter 6
CONTINUOUS PROBABILITY DISTRIBUTIONS6.1
the Uniform Probability Distribution6.2
The Normal Probability Distribution6.3
Normal approximation of Binomial Probabilities6.4
The Exponential Probability DistributionChapter 7
SAMPLING AND SAMPLING DISTRIBUTIONS7.1
The Electronics Associates Sampling Problem7.2
Simple Random Sampling7.3
Point Estimation7.4
Introduction to Sampling distributions7.5
Sampling distribution of 7.6
Sampling distribution of 7.7
Properties of Point Estimators7.8
Other Sampling MethodsChapter 8
INTERVAL ESTIMATION8.1
Interval Estimation of a Population Mean: Large-Sample Case8.2
Interval Estimation of a Population Mean: small-Sample Case8.3
Determining the Sample size8.4
Interval Estimation of a Population ProportionChapter 9
HYPOTHESIS TESTING9.1
Developing Null and Alternative Hypotheses9.2
Type I and Type II Errors9.3
One-Tailed Tests About a Population Mean: Large-Sample Case9.4
Two-Tailed Tests About a Population Mean: Large-Sample Case9.5
Tests about a Population Mean: small-Sample Case9.6
Tests about a Popultion Proportion9.7
Hypothesis Testing and DecisionMaking9.8
Calculating the Probability of Type II Errors9.9
Determining the Sample size for a Hypothesis Test About a PopulationChapter 10 STATISTICAL INFERENCE
ABOUT MEANS AND PROPORTIONS WITH TWO POPULATIONS10.1
Estimation of the Difference between the Means of Two Populations: Independent Samples10.2
Hypothesis Tests about the Difference between the
Means of Two Populations: Independent Samples10.3
Inferences about the Difference between the Means of Two Populations: Matched Samples10.4
Inferences about the difference between the Proportions of Two PopulationsChapter 11
INFERENCES ABOUT POPULATION VARIANCES11.1
Inferences about a Population Variance11.2
Inferences about the Variances of Two PopulationsChapter 12
TESTS OF GOODNESS OF FIT AND INDEPENDENCE12.1
Goodness of fit Test: A Multinomial Ppulation12.2
Test of Independence: contingency Tables12.3
Goodness of fit Test: Poisson and Normal distributionsChapter 13
ANALYSIS OF VARIANCE AND EXPERIMENTAL DESIGN13.1
An Introduction to analysis of Variance13.2 Analysis of Variance: Testing for the Equality of k Population Means13.3
Multiple comparison Procedures13.4
An Introduction to Experimental Design13.5
completely Randomized Designs13.6
Randomized Block Design13.7
Factoril ExperimentsChapter 14
SIMPLE LINEAR REGRESSION14.1
The Simple Linear Regression Model14.2
The Least Squares Method14.3
The coefficient of Determination14.4
Model Assumptions14.5
Testing for Significance14.6
Using the Estimated Regression Equation for Estimation and Prediction 14.7
Computer Solution of Regression Problems14.8
Residual Analysis: Testing Model Assumptions14.9
Residual analysis: Outliers and Influential ObservationsChapter 15
MULTIPLE REGRESSION15.1
The Multiple Regression Model15.2
The Least Squares Method15.3
The Multiple Coefficient of Determination15.4
Model Assumptions15.5
Testing for significance15.6
Using the Estimated Regression Equation for Estimation and Prediction 15.7
qualitative Indepedent Variables15.8
Residul anlysisChapter 16
REGRESSION ANALYSIS: MODEL BUILDING16.1
The General Linear Model16.2
Determining when to Add or Delete Variables16.3
First Steps in the analysis of a Larger Problem16.4
Variable-Selection Procedures16.5
Residual Analysis16.6
Multiple Regression approach to Analysis of Variance and Experimental DesignChapter 17
INDEX NUMBERS17.1
Price Relatives17.2
aggregate Price Indexes17.3
computing an Aggregate Index from Price Relatives17.4
Some Important Price Indexes17.5
Deflating a Series by Price Indexes17.6
Price Indexes: Other considerations17.7
quantity IndexesChapter 18
FORECASTING18.1
The Components of a Time Series18.2
Using smoothing Methods in forecasting18.3
Using Trend Projection in forecasting18.4
Using Trend and Seasonal components in Forecasting18.5
Using Regression Analysis in Forecasting18.6
Qualitative Approches to ForecastingChapter 19
NONPARAMETRIC METHODS19.1
sign Text19.2
Wilcoxon Signed-rnk Test19.3
Mann-Whitney-Wilcoxon Test19.4
Kruskal-Wallis Test19.5
Rank CorrelationChapter 20
STATISTICAL METHODS FOR QUALITY CONTROL20.1
Statistical Process Control20.2
Acceptance amplingChapter 21
SAMPLE SURVEY21.1
Terminology Used in Sample Surveys21.2
Types of Surveys and Sampling Methods21.3
Survey Errors21.4
simple Random Sampling21.5
Stratified simple Random Sampling21.6
cluster Sampling 21.7
Systematic samplingChapter 22
DECISION ANALYSIS22.1
Structuring the Decision Problem22.2
Decision Making with Probabilities22.3
Expected Value of Perfect Information22.4
Decision Analysis With Sample Information22.5
Developing a Decision strategy''22.6
Expected Value of Sample InformationAppendixesA. Reference and BiliographyB. TablesC. summtion NotationD. the Data DiskE. Answers to Even-Numbered ExercisesF. solutions to Self-Test Exercises
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