multi-cycle sampling

简明释义

多循环取样

英英释义

例句

1.The research team employed multi-cycle sampling to ensure diverse participant representation in the study.

研究团队采用了多周期抽样以确保研究中参与者的多样性。

2.The survey results improved significantly due to the implementation of multi-cycle sampling techniques.

由于实施了多周期抽样技术，调查结果显著改善。

3.Using multi-cycle sampling allowed the researchers to track changes in attitudes over time.

使用多周期抽样使研究人员能够跟踪态度随时间的变化。

4.By utilizing multi-cycle sampling, we can gather more comprehensive data over different time periods.

通过利用多周期抽样，我们可以在不同时间段收集更全面的数据。

5.The effectiveness of multi-cycle sampling was evident in the varied responses collected from different demographics.

在从不同人口统计中收集的多样化反馈中，多周期抽样的有效性显而易见。

作文

In the field of research and data collection, various methodologies are employed to ensure accuracy and reliability. One such method is multi-cycle sampling, which refers to the process of collecting data in multiple rounds or cycles to enhance the robustness of the findings. This technique is particularly useful in longitudinal studies where researchers aim to observe changes over time. By utilizing multi-cycle sampling (多周期抽样), researchers can gather a more comprehensive dataset that reflects the dynamics of the subject being studied.The primary advantage of multi-cycle sampling is its ability to minimize bias and improve the representativeness of the sample. In traditional sampling methods, a single round of data collection may fail to capture the diversity of opinions or behaviors within a population. However, by implementing multi-cycle sampling (多周期抽样), researchers can reach different segments of the population across various time points. This approach allows for a more nuanced understanding of trends and patterns, as it accounts for temporal variations that may influence the results.For instance, consider a study aimed at assessing public opinion on climate change. If researchers were to conduct a one-time survey, they might capture a snapshot of opinions at that moment. However, public sentiment can shift significantly due to recent events, policy changes, or media coverage. By applying multi-cycle sampling (多周期抽样), researchers can collect data at multiple intervals, enabling them to track shifts in public opinion over time. This longitudinal perspective not only enriches the analysis but also provides valuable insights for policymakers and stakeholders.Moreover, multi-cycle sampling can enhance the reliability of qualitative research. In qualitative studies, where interviews or focus groups are conducted, the richness of data often depends on the depth and breadth of perspectives gathered. By engaging participants in multiple cycles, researchers can delve deeper into their experiences and gather more comprehensive narratives. This iterative process fosters trust and rapport between researchers and participants, leading to more candid and informative responses.However, implementing multi-cycle sampling (多周期抽样) is not without its challenges. It requires careful planning and resource allocation, as conducting multiple rounds of data collection can be time-consuming and costly. Researchers must also consider the potential for participant attrition, as individuals may drop out of the study after the initial cycle. To mitigate these risks, it is essential to establish clear protocols for recruitment and retention, ensuring that the sample remains representative throughout the study.In conclusion, multi-cycle sampling (多周期抽样) is a powerful methodological approach that enhances the quality and reliability of research findings. By collecting data in multiple cycles, researchers can capture the complexities of human behavior and social phenomena over time. This technique not only improves the representativeness of the sample but also provides valuable insights into trends and shifts within the population. As research continues to evolve, embracing innovative methodologies like multi-cycle sampling will be crucial for addressing the multifaceted challenges of contemporary studies.

在研究和数据收集领域，采用各种方法以确保准确性和可靠性。其中一种方法是多周期抽样，指的是在多个轮次或周期中收集数据，以增强发现的稳健性。这种技术在纵向研究中尤其有用，研究人员旨在观察随时间变化的情况。通过利用多周期抽样，研究人员可以收集更全面的数据集，反映被研究主题的动态。多周期抽样的主要优点是能够最小化偏差并提高样本的代表性。在传统抽样方法中，一次数据收集可能无法捕捉到人群中意见或行为的多样性。然而，通过实施多周期抽样，研究人员可以在不同的时间点接触到人群的不同部分。这种方法允许对趋势和模式进行更细致的理解，因为它考虑了可能影响结果的时间变化。例如，考虑一项旨在评估公众对气候变化看法的研究。如果研究人员进行一次性调查，他们可能会捕捉到那个时刻的意见快照。然而，公众情绪可能由于最近事件、政策变化或媒体报道而显著转变。通过应用多周期抽样，研究人员可以在多个时间间隔收集数据，使他们能够跟踪公众意见随时间的变化。这种纵向视角不仅丰富了分析，还为政策制定者和利益相关者提供了宝贵的见解。此外，多周期抽样还可以增强定性研究的可靠性。在定性研究中，当进行访谈或焦点小组讨论时，数据的丰富性通常取决于收集到的观点的深度和广度。通过在多个周期中与参与者互动，研究人员可以更深入地探讨他们的经历，并收集更全面的叙述。这种迭代过程促进了研究人员与参与者之间的信任和融洽关系，导致更坦诚和信息丰富的回应。然而，实施多周期抽样并非没有挑战。它需要仔细的规划和资源分配，因为进行多轮数据收集可能耗时且成本高昂。研究人员还必须考虑参与者流失的可能性，因为个人可能在初始周期后退出研究。为了减轻这些风险，建立明确的招募和保留协议至关重要，确保样本在整个研究过程中保持代表性。总之，多周期抽样是一种强大的方法论方法，可以提高研究发现的质量和可靠性。通过在多个周期中收集数据，研究人员可以捕捉到人类行为和社会现象随时间变化的复杂性。这种技术不仅改善了样本的代表性，还提供了关于人群内部趋势和变化的宝贵见解。随着研究的不断发展，采用像多周期抽样这样的创新方法将对应对当代研究的多方面挑战至关重要。