统计学

章节摘录

版权页：   插图：   Example 7.5 Exit Polls （see Chapter 7） When an election for political office takes place， the television networks cancel regular programming and provide election coverage instead. When the ballots are counted， the results are reported. However， for important offices such as president or senator in large states， the networks actively compete to see which will be the first to predict a winner. This is done through exit polls， wherein a random sample of voters who exit the polling booth is asked for whom they voted. From the data the sample proportion ofvoters supporting the candidates is computed. A statistical technique is applied to determine whether there is enough evidence to infer that the leading candidate will garner enough votes to win. Suppose that the exit poll results from the state of Florida during the 2000 year elections were recorded.Although there were a number of candidates running for president， the exit pollsters recorded only the votes of the two candidates who had any chance of winning， the Republican candidate George W. Bush and the Democrat Albert Gore. The results （765 people who voted for either Bush or Gore） were stored on a file on the disk. The network analysts would like to know whether they can conclude that George W. Bush will win the state of Florida. Example 7.5 describes a very common application of statistical inference. The population the television networks wanted to make inferences about is the approximately 5 million Floridians who voted for Bush or Gore for president.The sample consisted of the 765 people randomly selected by the polling company who voted for either of the two main candidates. The characteristic of the population that we would like to know is the proportion of the Florida total electorate that voted for Bush. Specifically， we would like to know whether more than 50% of the electorate voted for Bush （counting only those who voted for either the Republican or Democratic candidate）. It must be made clear that， because we will not ask every one of the 5 million actual voters for whom they voted， we cannot predict the outcome with 100% certainty. This is a fact that statistics practitioners and even students of statistics must understand. A sample that is only a small fraction of the size of the population can lead to correct inferences only a certain percentage'of the time. You will find that statistics practitioners can control that fraction and usually set it between 90% and 99%.

内容概要

杰拉德·凯勒博士是罗瑞尔大学讲授统计学、管理科学和运筹管理学的教授。同时，他还任教于多伦多大学、迈阿密大学、麦克马斯特大学、温莎大学和北京科技大学。凯勒教授还曾担任银行关于信用卡计分和信用卡违约方面的咨询顾问并曾参与加拿大政府关于能源消耗方面的市场调查。    凯勒教授曾出版过Appfied Statistics with Microsoft Excel一书，并在OMEGA，IIE Transactions，Decision Sconces，INFOR，Economics Letters等杂志上发表过文章。1997—2000年间，他还在温莎大学为金融分析师举办的论坛上担任讲师。    凯勒教授的《统计学》一书自1988年出版以来，受到统计学师生和在工作中需要统计学知识的管理人员的好评，已经再版7次。

书籍目录

Preface
Guided Book Tour
1 What Is Statistics
2 Numerical Descriptive Techniques
3 Data Collection and Sampling
4 Sampling Distributions
5 Introduction to Estimation
6 Introduction to Hypothesis Testing
7 Inference about a Population
8 Inference about Comparing Two Populations
9 Analysis of Variance
10 Simple Linear Regression and correlation

编辑推荐

《经济学经典教材•核心课系列:统计学在经济和管理中的应用(第8版)》由杰拉德•凯勒著，与其他看重数理推导的统计学书籍不同，这本全球最畅销的管理统计学书籍强调商业统计在实践中的应用，希望通过实例教会学生如何选择正确的统计方法来分析实际问题。

作者简介

《经济学经典教材•核心课系列:统计学在经济和管理中的应用(第8版)》涵盖了描述统计法、假设检验、方差分析、回归分析、非参数统计方法、时间序列分析和决策分析等重要的统计方法。在介绍每一个统计方法时，作者杰拉德•凯勒博士首先介绍原理，然后采用其独特的解题步骤向学生演示如何应用统计方法解决实际问题：识别（识别问题的目标和数据类型），计算（手工计算和使用Excel、Minitab等软件计算）和解释（结合实际背景解释计算结果）。这种方法有利于提高学生的理解和技能，同时提供最大的灵活性。结合各项业务职能领域，通过例子、习题和案例，展示了市场营销经理、财务分析师、会计师、经济师以及其他管理人员是如何应用统计方法的。

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