aggregate method; overall method

简明释义

综合法

英英释义

例句

1.The overall method 整体方法 adopted in the evaluation process helped streamline decision-making.

在评估过程中采用的整体方法 overall method有助于简化决策过程。

2.For the financial analysis, we utilized an aggregate method 汇总方法 to summarize the quarterly earnings.

在财务分析中，我们利用汇总方法 aggregate method来总结季度收益。

3.The research team decided to use the aggregate method 汇总方法 to analyze the survey data for more accurate results.

研究团队决定使用汇总方法 aggregate method来分析调查数据，以获得更准确的结果。

4.In order to evaluate the project’s success, the manager implemented an overall method 整体方法 that considered all aspects of performance.

为了评估项目的成功，经理实施了一种整体方法 overall method，考虑了所有绩效方面。

5.Using an aggregate method 汇总方法 allows us to combine different datasets into a single comprehensive report.

使用汇总方法 aggregate method可以将不同的数据集合并为一份全面的报告。

作文

In the realm of data analysis and research methodologies, the terms aggregate method (聚合方法) and overall method (整体方法) play crucial roles in how we interpret and present data. Understanding these methods is essential for anyone looking to conduct thorough research or analysis. The aggregate method involves collecting individual data points and combining them to form a comprehensive picture. This approach is particularly useful when dealing with large datasets where individual data may not provide a clear understanding of trends or patterns. For instance, in a study examining the performance of students across various schools, using the aggregate method allows researchers to analyze overall trends in student performance rather than focusing solely on individual scores. By aggregating the data, one can identify whether there are systemic issues affecting multiple schools or if certain practices lead to better educational outcomes.On the other hand, the overall method refers to a broader approach that encompasses various aspects of data analysis. This method not only considers aggregated data but also integrates qualitative insights and contextual factors that may influence the results. For example, when evaluating the effectiveness of a new teaching strategy, an overall method would include both quantitative data from test scores and qualitative feedback from students and teachers. This holistic view enables researchers to understand the full impact of the teaching strategy, considering not just the numbers but also the experiences of those involved.Both methods have their strengths and weaknesses. The aggregate method is straightforward and can yield quick insights, making it ideal for preliminary analyses. However, it may overlook nuances that are critical for a deeper understanding of the data. Conversely, while the overall method provides a richer context, it can be time-consuming and complex, requiring more resources and careful planning.In practice, many researchers find that a combination of both methods yields the best results. By starting with the aggregate method, they can identify key trends and areas of interest, which can then be explored further using the overall method. This layered approach allows for a more comprehensive understanding of the data and can lead to more informed decisions and recommendations.As we continue to navigate an increasingly data-driven world, mastering these methodologies will become even more important. Whether in academic research, business analysis, or public policy, the ability to effectively utilize the aggregate method and the overall method will empower individuals and organizations to make data-informed decisions that can lead to positive outcomes. In conclusion, understanding the distinction and interplay between the aggregate method and the overall method is vital for anyone engaged in research and analysis. By leveraging both approaches, we can gain a clearer picture of the complexities within our data and ultimately drive better results in our respective fields.

在数据分析和研究方法论的领域中，术语aggregate method（聚合方法）和overall method（整体方法）在我们解释和呈现数据时发挥着至关重要的作用。理解这些方法对于任何希望进行深入研究或分析的人来说都是必不可少的。aggregate method涉及收集单个数据点并将其结合以形成全面的图景。这种方法在处理大量数据集时特别有用，因为单个数据可能无法清晰地理解趋势或模式。例如，在一项研究中检查各学校学生的表现时，使用aggregate method使研究人员能够分析学生表现的整体趋势，而不是仅仅关注个别成绩。通过聚合数据，人们可以识别出是否存在影响多所学校的系统性问题，或者某些实践是否导致更好的教育成果。另一方面，overall method指的是一种更广泛的方法，涵盖了数据分析的各个方面。这种方法不仅考虑聚合数据，还整合了可能影响结果的定性见解和背景因素。例如，在评估新教学策略的有效性时，overall method将包括来自测试分数的定量数据以及来自学生和教师的定性反馈。这种整体视角使研究人员能够理解教学策略的全面影响，不仅考虑数字，还考虑参与者的体验。这两种方法各有优缺点。aggregate method简单明了，可以快速产生洞察，非常适合初步分析。然而，它可能忽略对深入理解数据至关重要的细微差别。相反，虽然overall method提供了更丰富的背景，但它可能耗时且复杂，需要更多的资源和谨慎的规划。在实践中，许多研究人员发现结合这两种方法能获得最佳结果。通过从aggregate method开始，他们可以识别关键趋势和感兴趣的领域，然后利用overall method进一步探索。这种分层方法使我们能够更全面地理解数据，从而得出更明智的决策和建议。随着我们继续在一个日益数据驱动的世界中航行，掌握这些方法论将变得更加重要。无论是在学术研究、商业分析还是公共政策中，有效利用aggregate method和overall method的能力将使个人和组织能够做出基于数据的决策，从而带来积极的结果。总之，理解aggregate method和overall method之间的区别和相互关系对于参与研究和分析的任何人来说都是至关重要的。通过利用这两种方法，我们可以更清晰地了解数据中的复杂性，并最终推动我们各自领域的更好结果。