additional sampling

简明释义

1. 补充采样; 2. 附加采样; 3. 追加抽样;

英英释义

例句

1.Due to unexpected variations, the scientists opted for additional sampling 额外取样 to gather more comprehensive data.

由于意外的变异，科学家选择进行额外取样以收集更全面的数据。

2.To improve the reliability of the survey, we will perform additional sampling 额外取样 in different regions.

为了提高调查的可靠性，我们将在不同地区进行额外取样。

3.The researchers decided to conduct additional sampling 额外取样 to ensure the accuracy of their data.

研究人员决定进行额外取样以确保数据的准确性。

4.After reviewing the initial results, the team recommended additional sampling 额外取样 to strengthen their findings.

在审查初步结果后，团队建议进行额外取样以增强他们的发现。

5.The quality control department requested additional sampling 额外取样 of the product batches before approval.

质量控制部门在批准之前要求对产品批次进行额外取样。

作文

In the field of research and data analysis, the concept of additional sampling plays a crucial role in enhancing the reliability and validity of findings. Additional sampling refers to the process of collecting more data points beyond the initial set to improve the robustness of the results. This practice is particularly important in various fields such as social sciences, medicine, and market research, where the accuracy of conclusions can significantly impact decision-making processes.The necessity for additional sampling often arises when the initial sample size is deemed insufficient to draw meaningful conclusions. For instance, in a medical study investigating the effectiveness of a new drug, researchers may start with a small group of participants. If the results from this initial group show promise, they might decide to conduct additional sampling to include a larger and more diverse population. This helps ensure that the findings are not just applicable to a narrow demographic but can be generalized to a wider audience.Moreover, additional sampling can help identify outliers or anomalies in the data that may skew results. By expanding the sample size, researchers can better understand the variability within the data and make more informed interpretations. For example, in market research, a company may initially survey a limited number of consumers about their product preferences. If the feedback is overwhelmingly positive, they may choose to conduct additional sampling to confirm these results across different regions or demographics, ensuring that the positive response is not an isolated incident.Another significant advantage of additional sampling is its ability to enhance the statistical power of a study. Statistical power refers to the likelihood that a study will detect an effect if there is one to be detected. A larger sample size increases the chances of identifying true effects and reduces the risk of Type II errors, which occur when a study fails to detect an effect that is present. Therefore, implementing additional sampling can lead to more accurate and reliable outcomes, ultimately contributing to the advancement of knowledge in a particular field.However, it is essential to approach additional sampling with careful consideration of the methodology. Researchers must ensure that the additional data collected is relevant and representative of the population being studied. Poorly designed sampling strategies can lead to biased results and undermine the integrity of the research. For instance, if a survey on consumer behavior only targets a specific age group during additional sampling, the conclusions drawn may not reflect the preferences of the entire population.In conclusion, additional sampling is a vital component of effective research practices. It enhances the credibility of findings, ensures broader applicability of results, and increases statistical power. By carefully considering the design and execution of additional sampling, researchers can contribute valuable insights to their respective fields, ultimately leading to informed decision-making and advancements in knowledge. As we continue to navigate an increasingly complex world, the importance of robust data collection methods, including additional sampling, cannot be overstated.

在研究和数据分析领域，额外抽样的概念在增强研究结果的可靠性和有效性方面发挥着至关重要的作用。额外抽样是指在初始数据集之外收集更多数据点的过程，以改善结果的稳健性。这一做法在社会科学、医学和市场研究等多个领域尤为重要，因为结论的准确性可能会对决策过程产生重大影响。额外抽样的必要性通常出现在初始样本量被认为不足以得出有意义的结论时。例如，在一项研究新药有效性的医学研究中，研究人员可能会从一小组参与者开始。如果这一初始组的结果显示出希望，他们可能决定进行额外抽样，以纳入一个更大且更具多样性的人群。这有助于确保研究结果不仅适用于狭窄的人群，而可以推广到更广泛的受众。此外，额外抽样还可以帮助识别数据中的离群值或异常值，这些离群值可能会扭曲结果。通过扩大样本量，研究人员可以更好地理解数据中的变异性，并做出更明智的解释。例如，在市场研究中，一家公司可能最初针对有限数量的消费者进行调查，以了解他们的产品偏好。如果反馈极其积极，他们可能会选择进行额外抽样，以确认这些结果在不同地区或人群中的有效性，从而确保积极的反应不是孤立事件。额外抽样的另一个显著优势是能够增强研究的统计能力。统计能力是指研究在存在可检测效应的情况下发现效应的可能性。较大的样本量增加了识别真实效应的机会，并降低了第二类错误的风险，即研究未能检测到存在的效应。因此，实施额外抽样可以导致更准确和可靠的结果，最终有助于推动特定领域知识的进步。然而，必须谨慎考虑方法论来进行额外抽样。研究人员必须确保收集的额外数据与所研究的人群相关且具有代表性。设计不当的抽样策略可能导致结果偏倚，破坏研究的完整性。例如，如果一项关于消费者行为的调查在额外抽样期间仅针对特定年龄组，得出的结论可能无法反映整个群体的偏好。总之，额外抽样是有效研究实践的重要组成部分。它增强了研究结果的可信度，确保了结果的更广泛适用性，并提高了统计能力。通过仔细考虑额外抽样的设计和执行，研究人员可以为各自领域贡献有价值的见解，最终促成明智的决策和知识的进步。随着我们继续在日益复杂的世界中航行，健全的数据收集方法，包括额外抽样的重要性不容小觑。