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相关概念视频

Weighted Mean00:57

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While taking the arithmetic, geometric, or harmonic mean of a sample data set, equal importance is assigned to all the data points. However, all the values may not always be equally important in some data sets. An intrinsic bias might make it more important to give more weightage to specific values over others.
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What are Estimates?01:06

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It isn't easy to measure a parameter such as the mean height or the mean weight of a population. So, we draw samples from the population and calculate the mean height or mean weight of the individuals in the sample. This sample data acts as a representative measure of the population parameter. These sample statistics are known as estimates. 
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Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
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Estimating Population Mean with Unknown Standard Deviation01:22

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In practice, we rarely know the population standard deviation. In the past, when the sample size was large, this did not present a problem to statisticians. They used the sample standard deviation s as an estimate for σ and proceeded as before to calculate a confidence interval with close enough results. However, statisticians ran into problems when the sample size was small. A small sample size caused inaccuracies in the confidence interval.
William S. Gosset (1876–1937) of the...
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The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...
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When the population standard deviation is unknown and the sample size is large, the sample standard deviation s is commonly used as a point estimate of σ. However, it can sometimes under or overestimate the population standard deviation. To overcome this drawback, confidence intervals are determined to estimate population parameters and eliminate any calculation bias accurately. However, this only applies to random samples from normally distributed populations. Knowing the sample mean and...
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民主效应:一个基于权重的估计策略.

Pedro Dal Bó1, Andrew Foster2, Kenju Kamei3

  • 1Brown University and NBER.

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|August 13, 2025
PubMed
概括
此摘要是机器生成的。

与强加的政策相比,民主可以提高政策的有效性. 使用人口流行权重的新估计策略简化了分析,并在特定条件下消除了选择效应.

关键词:
C1 一个人的心态C9 C9 C9 C9 C9 C9 C9 C9 C9 C9 C9 C9 C9 C9 C9 C9 C9 C9 C9D7 D7 D7 D7 D7 D7 D7 D7 D7 D7 D7 D7 D7 D7民主效应是一种效应.实验 实验 实验 实验测量方法 测量方法选择效应的选择效应投票时间 投票时间

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科学领域:

  • 行为经济学是一种行为经济学.
  • 实验经济学是一种实验经济学.
  • 政治经济学的政治经济学.

背景情况:

  • 民主的政策选择可能会产生比外部施加更大的效果.
  • 以前的估计策略需要来自外部治疗的详细投票数据.

研究的目的:

  • 为民主效应引入一个更简单的估计策略.
  • 消除在民主制度下评估政策有效性的选择效应.
  • 将新策略应用于现有和新型实验数据.

主要方法:

  • 开发使用人口流行率的基于权重的估计器.
  • 导出新估计器的统计分布.
  • 将估计器应用于Dal Bó等人. (2010) 数据和一个新的实验.

主要成果:

  • 新策略通过消除对外处理投票数据的需求,简化了估计.
  • 在Dal Bó等人身上发现了显著的民主效应. (2010) 的数据.
  • 在新的实验数据中没有发现显著的民主效应.

结论:

  • 基于权重的估计策略是分析民主效应的可行替代方案.
  • 民主效应的存在可能取决于实验设计和数据的可用性.
  • 进一步的研究可以探索选择效应被消除的条件.