all in aggregate

简明释义

1. 砂砾集合伐; 2. 天然混合集料;

英英释义

例句

1.When analyzing the performance metrics all in aggregate, we realized some areas needed improvement.

在分析绩效指标时，总体而言，我们意识到一些领域需要改进。

2.The survey results, all in aggregate, indicate a strong preference for remote work among employees.

调查结果总体而言，表明员工对远程工作的强烈偏好。

3.The company's profits, when considered all in aggregate, show a significant increase this quarter.

当考虑总体而言，公司的利润在本季度显示出显著增长。

4.If we look at the data all in aggregate, we can see a clear trend towards sustainability.

如果我们从总体来看这些数据，就可以看到向可持续发展明显的趋势。

5.The all in aggregate costs of the project exceeded our initial budget estimates.

该项目的费用总体而言超出了我们最初的预算估算。

作文

In the world of data analysis and research, the phrase all in aggregate plays a crucial role in summarizing information. When we look at large sets of data, we often need to draw conclusions that reflect the overall trends rather than focusing on individual data points. For example, when evaluating the performance of a company's sales over several years, it is more insightful to analyze the figures all in aggregate, rather than getting lost in the fluctuations of monthly sales. This approach allows researchers and business analysts to identify patterns and make informed decisions based on the broader picture.The concept of looking at data all in aggregate also applies to various fields, including economics, healthcare, and environmental studies. In economics, policymakers often rely on aggregated data to assess the health of the economy. For instance, they may look at GDP growth rates, unemployment rates, and inflation all in aggregate to understand the economic landscape. This holistic view helps them craft policies that can effectively address issues affecting multiple sectors simultaneously.Similarly, in healthcare, researchers frequently analyze patient outcomes all in aggregate to determine the effectiveness of treatments across diverse populations. By examining data from thousands of patients, they can identify which treatments yield the best results overall, rather than just for specific individuals. This comprehensive analysis is crucial for developing guidelines that improve healthcare delivery and patient outcomes.Environmental studies also benefit from the principle of analyzing data all in aggregate. For example, when assessing climate change impacts, scientists collect data from various sources, such as temperature records, ice core samples, and sea level measurements. By considering these factors all in aggregate, researchers can draw more accurate conclusions about the state of the planet and the urgency of addressing climate issues.However, while analyzing data all in aggregate provides valuable insights, it is essential to acknowledge its limitations. Aggregated data can sometimes obscure significant variations within subgroups. For instance, if a study on educational outcomes reports average test scores all in aggregate, it may hide disparities among different demographic groups. Therefore, it is crucial for researchers to balance aggregate analysis with deeper investigations into specific subsets of data to ensure that no important details are overlooked.In conclusion, the phrase all in aggregate encapsulates the importance of viewing data as a whole to draw meaningful conclusions. Whether in business, economics, healthcare, or environmental science, analyzing information all in aggregate enables us to identify trends, make informed decisions, and develop effective strategies. However, it is equally important to remain aware of the nuances that may be hidden within the aggregate data, ensuring that our analyses are both comprehensive and inclusive. By embracing this dual approach, we can better understand the complexities of our world and work towards solutions that benefit all segments of society.

在数据分析和研究的世界中，短语all in aggregate在总结信息时发挥着至关重要的作用。当我们查看大量数据集时，我们常常需要得出反映整体趋势的结论，而不是关注单个数据点。例如，在评估一家公司的销售业绩时，分析这些数字all in aggregate往往比迷失在每月销售波动中更具洞察力。这种方法使研究人员和商业分析师能够识别模式，并根据更广泛的背景做出明智的决策。查看数据all in aggregate的概念还适用于多个领域，包括经济学、医疗保健和环境研究。在经济学中，政策制定者通常依赖汇总数据来评估经济的健康状况。例如，他们可能会查看GDP增长率、失业率和通货膨胀率all in aggregate以了解经济形势。这种整体视角帮助他们制定能够有效应对影响多个部门的问题的政策。同样，在医疗保健领域，研究人员经常分析患者结果all in aggregate以确定治疗在不同人群中的有效性。通过检查成千上万患者的数据，他们可以识别哪些治疗方法总体上产生最佳效果，而不仅仅是针对特定个体。这种全面的分析对于制定改善医疗服务和患者结果的指南至关重要。环境研究也受益于分析数据all in aggregate的原则。例如，在评估气候变化影响时，科学家从温度记录、冰芯样本和海平面测量等各种来源收集数据。通过将这些因素all in aggregate考虑在内，研究人员可以得出关于地球状态和解决气候问题紧迫性的更准确结论。然而，尽管分析数据all in aggregate提供了有价值的见解，但承认其局限性也是至关重要的。汇总数据有时会掩盖子组之间的显著差异。例如，如果一项关于教育成果的研究报告平均测试分数all in aggregate，这可能会掩盖不同人口群体之间的差距。因此，研究人员需要平衡汇总分析与对特定数据子集的深入调查，以确保没有重要细节被忽视。总之，短语all in aggregate概括了将数据视为整体以得出有意义结论的重要性。无论是在商业、经济学、医疗保健还是环境科学中，分析信息all in aggregate使我们能够识别趋势、做出明智决策并制定有效策略。然而，同样重要的是要意识到聚合数据中可能隐藏的细微差别，确保我们的分析既全面又包容。通过接受这种双重方法，我们可以更好地理解我们世界的复杂性，并朝着有利于社会各个层面的解决方案努力。