area sampling

简明释义

面积抽样;

英英释义

例句

1.By implementing area sampling, the survey team was able to gather data from diverse neighborhoods.

通过实施区域抽样，调查团队能够从不同的社区收集数据。

2.In agricultural studies, area sampling helps determine crop yields across different fields.

在农业研究中，区域抽样有助于确定不同田地的作物产量。

3.For the wildlife census, biologists employed area sampling to count animal populations in specific habitats.

为了进行野生动物普查，生物学家采用了区域抽样来统计特定栖息地的动物种群。

4.The government used area sampling to assess the living conditions in various districts of the city.

政府使用区域抽样来评估城市各个地区的生活条件。

5.The researchers decided to use area sampling to ensure that all regions of the park were represented in their study.

研究人员决定使用区域抽样以确保公园的所有区域在他们的研究中都有代表性。

作文

In the field of research and statistics, sampling methods play a crucial role in ensuring the accuracy and reliability of data collection. One such method is area sampling, which involves selecting samples based on specific geographical areas. This technique is particularly useful when the population being studied is spread out over a large region, making it impractical to conduct a complete census. By focusing on certain areas, researchers can gather representative data that reflects the characteristics of the larger population. The process of area sampling begins with dividing the entire study area into smaller, manageable segments or clusters. These segments can be defined by natural boundaries, such as rivers or mountains, or by man-made boundaries, such as city blocks or neighborhoods. Once the area is segmented, researchers can randomly select a few segments to sample from. This random selection is crucial as it helps eliminate bias and ensures that each segment has an equal chance of being chosen.One of the advantages of area sampling is its efficiency. Instead of surveying every individual in a large population, researchers can focus their efforts on a limited number of areas. This not only saves time but also reduces costs associated with data collection. For example, if a researcher wants to study the health outcomes of residents in a sprawling city, they might choose to survey only a few neighborhoods rather than trying to reach every resident across the entire city. This targeted approach allows for a more manageable and practical data collection process.Moreover, area sampling can enhance the quality of the data collected. By concentrating on specific areas, researchers can gain deeper insights into the local context, culture, and environment that may influence the study's outcomes. For instance, if a study aims to understand the impact of urban pollution on respiratory health, focusing on densely populated industrial areas might yield more relevant information than a random selection of individuals from the entire city.However, it is essential to recognize the limitations of area sampling. While this method can provide valuable insights, it may not capture the full diversity of the population if certain areas are overrepresented or underrepresented. Researchers must carefully consider how they define their segments and ensure that their sampling strategy accounts for any potential biases. Additionally, the findings from area sampling may not always be generalizable to the entire population, especially if the selected areas have unique characteristics that differ significantly from other regions.In conclusion, area sampling is a powerful tool in the arsenal of researchers and statisticians. Its ability to streamline data collection while providing meaningful insights into specific populations makes it an attractive option for many studies. However, like any sampling method, it requires careful planning and consideration to ensure that the results are valid and reliable. As researchers continue to explore complex social, economic, and environmental issues, methods like area sampling will remain essential in helping them draw accurate conclusions and make informed decisions based on their findings.

在研究和统计领域，抽样方法在确保数据收集的准确性和可靠性方面发挥着至关重要的作用。其中一种方法是区域抽样，它涉及根据特定的地理区域选择样本。这种技术在研究的人口分布在大区域时特别有用，因为进行完整普查是不切实际的。通过专注于某些区域，研究人员可以收集反映更大人群特征的代表性数据。区域抽样的过程始于将整个研究区域划分为较小的、可管理的段或集群。这些段可以通过自然边界（如河流或山脉）或人为边界（如城市街区或社区）来定义。一旦区域被分段，研究人员就可以随机选择几个段进行抽样。这种随机选择至关重要，因为它有助于消除偏见，并确保每个段都有相等的被选中机会。区域抽样的一个优点是其效率。研究人员无需在大人口中调查每个人，而是可以将精力集中在有限数量的区域上。这不仅节省了时间，还减少了与数据收集相关的成本。例如，如果研究人员想要研究一个广阔城市居民的健康结果，他们可能会选择只调查少数几个社区，而不是试图接触整个城市的每一位居民。这种有针对性的方法使数据收集过程更加可管理和实用。此外，区域抽样可以提高收集数据的质量。通过集中在特定区域，研究人员可以深入了解当地的背景、文化和环境，这些因素可能会影响研究的结果。例如，如果一项研究旨在了解城市污染对呼吸健康的影响，专注于人口稠密的工业区可能会比从整个城市随机选择个体获得更相关的信息。然而，必须认识到区域抽样的局限性。虽然这种方法可以提供有价值的见解，但如果某些区域过度代表或不足代表，可能无法捕捉到整个群体的多样性。研究人员必须仔细考虑如何定义他们的段，并确保他们的抽样策略考虑到任何潜在的偏见。此外，来自区域抽样的发现可能并不总是可以推广到整个群体，特别是如果所选区域具有与其他地区显著不同的独特特征。总之，区域抽样是研究人员和统计学家工具箱中的一种强大工具。它能够简化数据收集，同时提供对特定人群的有意义的见解，使其成为许多研究的有吸引力的选择。然而，像任何抽样方法一样，它需要仔细的规划和考虑，以确保结果的有效性和可靠性。随着研究人员继续探索复杂的社会、经济和环境问题，像区域抽样这样的方法将继续在帮助他们得出准确结论和根据研究结果做出明智决策方面发挥重要作用。