sampling procedure

简明释义

取样程序

英英释义

例句

1.In clinical trials, an effective sampling procedure 抽样程序 is crucial for obtaining valid results.

在临床试验中，有效的抽样程序 sampling procedure 对于获得有效结果至关重要。

2.To minimize bias, the team implemented a stratified sampling procedure 抽样程序 based on demographic factors.

为了最小化偏差，团队根据人口统计因素实施了分层抽样程序 sampling procedure。

3.The sampling procedure 抽样程序 used in this survey involved random selection from a list of participants.

本次调查中使用的抽样程序 sampling procedure 涉及从参与者名单中随机选择。

4.Understanding the sampling procedure 抽样程序 is key to interpreting the results of any study.

理解抽样程序 sampling procedure 是解读任何研究结果的关键。

5.The researchers designed a rigorous sampling procedure 抽样程序 to ensure the data collected was representative of the population.

研究人员设计了一套严格的抽样程序 sampling procedure，以确保收集的数据能够代表总体。

作文

In the field of research, the importance of a well-defined sampling procedure cannot be overstated. A sampling procedure refers to the method used to select individuals or items from a larger population for the purpose of conducting a study. This process is crucial because it directly influences the validity and reliability of the research findings. For instance, if a researcher aims to understand the eating habits of teenagers in a city, a random sampling procedure may be employed to ensure that every teenager has an equal opportunity of being selected. This helps to eliminate bias and ensures that the sample is representative of the entire population. On the other hand, if a researcher chooses to use a convenience sampling method, where only accessible teenagers are surveyed, the results may not accurately reflect the eating habits of all teenagers in the city. This highlights the significance of carefully considering the sampling procedure before commencing any research project.Moreover, different types of sampling procedures exist, including stratified sampling, systematic sampling, and cluster sampling. Stratified sampling involves dividing the population into distinct subgroups and then randomly selecting samples from each subgroup. This is particularly useful when researchers want to ensure that specific characteristics are represented in the sample. For example, if the researcher is interested in the eating habits of teenagers across different socio-economic backgrounds, stratified sampling would allow them to gather insights from various economic strata.Systematic sampling, on the other hand, involves selecting every nth individual from a list of the population. This method can be efficient and straightforward, but it assumes that the list is organized in a way that does not introduce bias. Lastly, cluster sampling involves dividing the population into clusters (often geographically) and then randomly selecting entire clusters for the study. This can be advantageous in large populations where it may be impractical to conduct a survey across the entire area.The choice of sampling procedure is influenced by several factors, including the research objectives, the nature of the population, and available resources. Researchers must weigh the pros and cons of each method to determine which will best serve their study. For instance, while random sampling is often seen as the gold standard, it may not always be feasible due to time constraints or logistical challenges. In such cases, alternative sampling procedures may be employed, but researchers must be cautious about the potential for bias and how it may affect their findings.In conclusion, the sampling procedure is a fundamental aspect of research design that can significantly impact the outcomes of a study. By understanding and implementing appropriate sampling procedures, researchers can enhance the credibility of their work and contribute valuable insights to their fields. Therefore, it is essential for anyone involved in research to have a solid grasp of various sampling procedures and their implications, ensuring that their findings are both valid and reliable. Ultimately, a thoughtful approach to the sampling procedure will lead to more accurate and meaningful research results, benefiting not only the researchers but also the broader community that relies on their findings.

在研究领域，一个明确的抽样程序的重要性不容小觑。抽样程序是指用于从更大人群中选择个体或项目以进行研究的方法。这个过程至关重要，因为它直接影响研究结果的有效性和可靠性。例如，如果研究者旨在了解城市青少年的饮食习惯，可以采用随机抽样程序，以确保每位青少年都有相等的被选中机会。这有助于消除偏见，并确保样本代表整个群体。另一方面，如果研究者选择使用便利抽样方法，仅调查可接触到的青少年，那么结果可能无法准确反映城市中所有青少年的饮食习惯。这突显了在开始任何研究项目之前仔细考虑抽样程序的重要性。此外，存在不同类型的抽样程序，包括分层抽样、系统抽样和聚类抽样。分层抽样涉及将人群划分为不同的子群体，然后从每个子群体中随机选择样本。当研究者希望确保特定特征在样本中得到代表时，这种方法特别有用。例如，如果研究者对不同社会经济背景的青少年饮食习惯感兴趣，分层抽样将使他们能够从各个经济阶层收集见解。系统抽样则涉及从人口清单中每隔n个个体进行选择。此方法可以高效且简单，但假设清单的组织方式不会引入偏见。最后，聚类抽样涉及将人群划分为聚类（通常是地理上的），然后随机选择整个聚类进行研究。在大规模人群中，这种方法可能是有利的，因为在整个区域进行调查可能不切实际。抽样程序的选择受多个因素的影响，包括研究目标、人口特性和可用资源。研究者必须权衡每种方法的优缺点，以确定哪种方法最能服务于他们的研究。例如，尽管随机抽样通常被视为金标准，但由于时间限制或后勤挑战，它可能并不总是可行。在这种情况下，可能会采用替代的抽样程序，但研究者必须谨慎考虑潜在的偏见及其对研究结果的影响。总之，抽样程序是研究设计的基本方面，可以显著影响研究结果。通过理解和实施适当的抽样程序，研究者可以增强其工作的可信度，并为其领域贡献有价值的见解。因此，任何参与研究的人都必须牢牢掌握各种抽样程序及其含义，确保他们的发现既有效又可靠。最终，对抽样程序的深思熟虑的处理将导致更准确和有意义的研究结果，这不仅有利于研究者，也有利于依赖其发现的更广泛社区。