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相关概念视频

Stratified Sampling Method01:16

Stratified Sampling Method

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...
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Cluster Sampling Method01:20

Cluster Sampling Method

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Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
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Sampling Plans01:23

Sampling Plans

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Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
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Design Example: Measuring Distance Between Two Points with Obstructions01:10

Design Example: Measuring Distance Between Two Points with Obstructions

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When measuring distances in areas with physical obstructions, such as a lake in a field, surveyors must employ techniques to calculate accurate lengths without direct line measurements. One effective method is the offset technique, which allows for precise distance estimation over inaccessible stretches.In this scenario, a surveyor must measure a side of an area that crosses a lake. Since the measuring tape cannot span the lake, the surveyor begins by establishing a baseline that aligns with...
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Types of Surveys01:27

Types of Surveys

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Surveys are essential for marking property boundaries near water bodies. Different types of surveys are defined, each with its own function. Land surveys mark the property boundaries, while route surveys determine the position of properties on nearby highways. Topographic surveys create maps by capturing the three-dimensional features of the land. Hydrographic surveys focus on the shapes of underwater areas and the movement of streams through the properties. Mine surveys determine the relative...
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Convenience Sampling Method00:55

Convenience Sampling Method

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population.
Convenience sampling is a non-random method of sample selection; this method selects individuals that are easily accessible and may result in biased data. For example, a marketing...
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Updated: Jul 11, 2025

Sampling Soils in a Heterogeneous Research Plot
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在分层采样中使用调查成本构建高效的层级边界.

Karuna G Reddy1, M G M Khan1

  • 1School of Information Technology, Engineering, Mathematics and Physics, The University of the South Pacific, Suva, Fiji.

Heliyon
|November 15, 2023
PubMed
概括
此摘要是机器生成的。

本研究引入了一种新的方法,用于确定分层采样中最佳的层边界 (OSB) 和样本大小 (OSS),特别是当调查成本是固定的时. 这种方法提高了估计人口参数 (如收入) 的精度.

关键词:
62-11-11 这是一个很好的例子.62D05 这是一个很好的例子.62P2525 这是一个很好的例子.91B82 它们是什么?动态编程 是一种动态编程.最好的分层是最优的分层.样本分配样本分配分层随机采样分层随机采样调查成本 调查成本 调查成本

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相关实验视频

Last Updated: Jul 11, 2025

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07:11

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科学领域:

  • 统计 统计 统计 统计
  • 调查方法 调查方法
  • 计量经济学 计量经济学

背景情况:

  • 分层抽样设计的目的是准确估计人口参数.
  • 最佳的层边界 (OSB) 和样本大小 (OSS) 对于最大化精度至关重要.
  • 在固定的总样本大小或预算限制下,现有的OSB/OSS方法可能不会保持最佳状态.

研究的目的:

  • 提出一种计算OSB和OSS的方法,考虑每单位层测量成本或概率密度函数.
  • 为了应对在固定调查预算下保持最佳分层的挑战.
  • 在分层调查中提高人口参数估计的准确性.

主要方法:

  • 开发了一种用于计算OSB和OSS的新方法,其中包含成本信息.
  • 采用基于设计的分层,使用HILDA调查数据集 (第18波).
  • 估计了澳大利亚每年的总可支配收入的平均值.
  • 提供了数值插图,以指数和直角三角分布.

主要成果:

  • 拟议的OSB和OSS计算方法即使具有固定的总样本大小和已知的成本,也是有效的.
  • 使用HILDA数据的实证应用证明了该方法对收入等与政策相关的变量有用.
  • 该技术在更新的stratifyR包中实现了实际应用.

结论:

  • 建议的方法提供了令人满意的结果,为现有技术提供了改进的或可比的效率.
  • 这种方法提高了分层调查中人口参数估计的准确性.
  • 该方法在不同的连续变量分布和实际调查约束中是稳健的.