Introduction to Estimation

David M. Lane
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引用次数: 1

Abstract

One of the major applications of statistics is estimating population parameters from sample statistics. For example, a poll may seek to estimate the proportion of adult residents of a city that support a proposition to build a new sports stadium. Out of a random sample of 200 people, 106 say they support the proposition. Thus in the sample, 0.53 of the people supported the proposition. This value of 0.53 is called a point estimate of the population proportion. It is called a point estimate because the estimate consists of a single value or point. The concept of degrees of freedom and its relationship to estimation is discussed in Section B. " Characteristics of Estimators " discusses two important concepts: bias and precision. Point estimates are usually supplemented by interval estimates called confidence intervals. Confidence intervals are intervals constructed using a method that contains the population parameter a specified proportion of the time. For example, if the pollster used a method that contains the parameter 95% of the time it is used, he or she would arrive at the following 95% confidence interval: 0.46 < π < 0.60. The pollster would then conclude that somewhere between 0.46 and 0.60 of the population supports the proposal. The media usually reports this type of result by saying that 53% favor the proposition with a margin of error of 7%. The sections on confidence intervals show how to compute confidence intervals for a variety of parameters. Prerequisites • Chapter 3 Measures of Central Tendency • Chapter 3: Variability Learning Objectives 1. Define statistic 2. Define parameter 3. Define point estimate 4. Define interval estimate 5. Define margin of error One of the major applications of statistics is estimating population parameters from sample statistics. For example, a poll may seek to estimate the proportion of adult residents of a city that support a proposition to build a new sports stadium. Out of a random sample of 200 people, 106 say they support the proposition. Thus in the sample, 0.53 of the people supported the proposition. This value of 0.53 is called a point estimate of the population proportion. It is called a point estimate because the estimate consists of a single value or point. Point estimates are usually supplemented by interval estimates called confidence intervals. Confidence intervals are intervals constructed using a method that contains the population parameter a specified proportion of the time. For …
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统计学的一个主要应用是从样本统计中估计总体参数。例如,一项民意调查可能试图估计一个城市的成年居民支持建立一个新体育场的提议的比例。在200人的随机抽样中,有106人表示支持这一提议。因此,在样本中,0.53的人支持这个命题。这个0.53的值称为总体比例的点估计值。它被称为点估计,因为估计由单个值或点组成。自由度的概念及其与估计的关系在b节中讨论。《估计量的特性》讨论了两个重要的概念:偏差和精度。点估计通常由称为置信区间的区间估计补充。置信区间是使用包含特定时间比例的总体参数的方法构造的区间。例如,如果民意调查者使用的方法95%的时间包含参数,他或她将得到以下95%置信区间:0.46 < π < 0.60。民意测验专家得出的结论是,大约有0.46到0.60的人支持这项提议。媒体在报道这类结果时,通常会说53%的人赞成该提议,误差幅度为7%。关于置信区间的部分展示了如何计算各种参数的置信区间。先决条件•第3章集中趋势的测量•第3章:可变性学习目标定义统计量2。定义参数3。定义点估计4。定义区间估计5。定义误差范围统计学的一个主要应用是从样本统计量估计总体参数。例如,一项民意调查可能试图估计一个城市的成年居民支持建立一个新体育场的提议的比例。在200人的随机抽样中,有106人表示支持这一提议。因此,在样本中,0.53的人支持这个命题。这个0.53的值称为总体比例的点估计值。它被称为点估计,因为估计由单个值或点组成。点估计通常由称为置信区间的区间估计补充。置信区间是使用包含特定时间比例的总体参数的方法构造的区间。为…
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