sampling method

简明释义

取样法

英英释义

例句

1.A convenience sampling method was used to quickly gather responses from available participants.

采用便利抽样方法迅速从可用参与者中收集反馈。

2.The survey's sampling method was criticized for not being representative of the entire population.

该调查的抽样方法因未能代表整个群体而受到批评。

3.Using a systematic sampling method, the team selected every tenth name from the list.

使用系统的抽样方法，团队从名单中选择了每第十个名字。

4.The researchers decided to use a random sampling method to ensure every participant had an equal chance of being selected.

研究人员决定使用随机抽样方法以确保每个参与者都有相等的被选中机会。

5.In market research, a stratified sampling method can help gather more accurate data from different demographic groups.

在市场研究中，分层抽样方法可以帮助从不同的人口群体中收集更准确的数据。

作文

In the field of research and statistics, the choice of a suitable sampling method is crucial for obtaining valid and reliable results. A sampling method refers to the technique used to select individuals or items from a larger population to participate in a study. The effectiveness of the research findings often hinges on how well the sample represents the population from which it is drawn. Therefore, understanding different sampling methods is essential for researchers aiming to draw meaningful conclusions from their data.There are several types of sampling methods, each with its own advantages and disadvantages. One common approach is random sampling, where every member of the population has an equal chance of being selected. This method minimizes bias and enhances the representativeness of the sample. However, achieving true random sampling can be challenging, especially in large populations where accessibility may be limited.Another widely used sampling method is stratified sampling. In this approach, the population is divided into distinct subgroups, or strata, that share similar characteristics. Researchers then randomly select samples from each stratum. This method ensures that specific subgroups are adequately represented, making it particularly useful in studies where certain demographics are crucial to the research question. However, stratified sampling requires detailed knowledge of the population's characteristics, which may not always be available.Systematic sampling is another technique that offers a structured approach to sample selection. In this sampling method, researchers select every nth individual from a list of the population. For example, if a researcher wants to survey 100 people from a list of 1,000, they might select every 10th person. While systematic sampling is easier to implement than random sampling, it can introduce bias if there is an underlying pattern in the population list that aligns with the sampling interval.Convenience sampling, though less rigorous, is often employed due to its practicality. This sampling method involves selecting individuals who are easiest to reach or readily available, such as friends, family, or colleagues. While this method is cost-effective and time-efficient, it often leads to significant biases, as the sample may not accurately reflect the broader population.In addition to these traditional sampling methods, researchers are increasingly utilizing online platforms for data collection, which introduces new challenges and opportunities. For instance, online surveys can reach a wide audience quickly; however, they may suffer from self-selection bias, as those who choose to participate may differ significantly from those who do not.In conclusion, the choice of sampling method is a fundamental aspect of research design that can significantly influence the validity of the findings. Researchers must carefully consider their objectives, the nature of the population, and the resources available when selecting a sampling method. By doing so, they can enhance the reliability of their results and contribute valuable insights to their respective fields. Ultimately, a well-chosen sampling method not only strengthens the research but also fosters trust in the conclusions drawn from the data collected.

在研究和统计领域，选择合适的抽样方法对于获得有效和可靠的结果至关重要。抽样方法是指用于从更大的人群中选择个体或项目以参与研究的技术。研究结果的有效性通常取决于样本在多大程度上代表了其所抽取的人口。因此，理解不同的抽样方法对旨在从数据中得出有意义结论的研究人员来说是必不可少的。有几种类型的抽样方法，每种方法都有其优缺点。一种常见的方法是随机抽样，在这种方法中，人口的每个成员都有相等的机会被选中。这种方法最小化了偏差，并增强了样本的代表性。然而，特别是在大型人口中，实现真正的随机抽样可能具有挑战性，因为可达性可能有限。另一种广泛使用的抽样方法是分层抽样。在这种方法中，人口被划分为具有相似特征的不同子组或层。研究人员然后从每个层中随机选择样本。这种方法确保特定子组得到充分代表，特别适用于某些人口统计信息对研究问题至关重要的研究。然而，分层抽样需要对人口特征有详细了解，而这些信息可能并不总是可用。系统抽样是另一种提供结构化样本选择的方法。在这种抽样方法中，研究人员从人口列表中选择每第n个个体。例如，如果研究人员想要从1000人的名单中调查100人，他们可能会选择每第10个人。虽然系统抽样比随机抽样更容易实施，但如果人口列表中存在与抽样间隔对齐的潜在模式，它可能会引入偏差。便利抽样虽然不那么严格，但由于其实用性，通常被采用。这种抽样方法涉及选择最容易接触到或随时可用的个体，比如朋友、家人或同事。虽然这种方法在成本和时间上都很有效，但它往往会导致显著的偏差，因为样本可能无法准确反映更广泛的人口。除了这些传统的抽样方法外，研究人员越来越多地利用在线平台进行数据收集，这带来了新的挑战和机遇。例如，在线调查可以迅速接触广泛的受众；然而，由于自我选择偏差，参与者可能与未参与者之间存在显著差异。总之，抽样方法的选择是研究设计的一个基本方面，可以显著影响发现的有效性。研究人员在选择抽样方法时必须仔细考虑他们的目标、人口的性质以及可用资源。通过这样做，他们可以增强结果的可靠性，并为各自领域贡献有价值的见解。最终，精心选择的抽样方法不仅增强了研究的可信度，而且促进了对从收集的数据得出的结论的信任。