partial average

简明释义

部分海损;分损

英英释义

例句

1.To calculate the student’s grade, we need to find the partial average 部分平均值 of their scores from the last three exams.

为了计算学生的成绩，我们需要找出他们最近三次考试的partial average 部分平均值。

2.In statistics, a partial average 部分平均值 can be useful when analyzing subsets of data.

在统计学中，分析数据子集时，partial average 部分平均值 是非常有用的。

3.We computed the partial average 部分平均值 of the last six months to assess the trend in customer satisfaction.

我们计算了过去六个月的partial average 部分平均值 以评估客户满意度的趋势。

4.The partial average 部分平均值 of the monthly expenses helped the team identify areas to cut costs.

每月开支的partial average 部分平均值 帮助团队识别削减成本的领域。

5.The report showed a partial average 部分平均值 of sales for the first quarter, which can help us project future earnings.

报告显示第一季度的partial average 部分平均值 销售额，这可以帮助我们预测未来的收益。

作文

In today's world, data analysis plays a crucial role in decision-making across various fields. One of the key concepts that often comes up in statistical analysis is the partial average. The term partial average refers to the average of a subset of data points within a larger dataset. This concept is particularly useful when we want to analyze specific segments of data without being influenced by the entire dataset's variations. For instance, in educational research, if we want to evaluate the performance of students in a particular class, we might calculate the partial average of their test scores instead of looking at the average scores of all students in the school. This allows for a more focused and relevant analysis.Understanding how to compute the partial average is essential for accurate data interpretation. To find the partial average, one must first identify the subset of data points that are of interest. After isolating these data points, you sum them up and then divide by the number of points in that subset. This process helps in understanding trends or patterns that may not be visible in the overall average. For example, if a company wants to assess the sales performance of a specific product line over a quarter, they would calculate the partial average of sales figures for that product line alone, rather than mixing it with other unrelated products.The significance of the partial average extends beyond mere calculations; it also aids in making informed decisions. In business, managers often rely on partial averages to gauge the effectiveness of marketing strategies targeted at specific demographics. By analyzing the partial average of customer feedback from a particular campaign, they can determine whether their efforts were successful and where improvements may be needed. This targeted approach ensures resources are allocated efficiently and effectively.Moreover, the partial average can also play a pivotal role in academic research. Researchers frequently need to focus on specific groups or conditions when studying complex phenomena. For example, in a medical study investigating the effects of a new drug, researchers might calculate the partial average of recovery times for patients within a certain age range. This allows them to draw conclusions that are more applicable to that demographic, rather than making broad generalizations that may not hold true for everyone.In conclusion, the partial average is a powerful tool in data analysis that provides deeper insights into specific segments of data. By focusing on subsets rather than the entire dataset, analysts can uncover meaningful patterns and trends that inform better decision-making. Whether in business, education, or research, understanding and utilizing the partial average can lead to more precise evaluations and outcomes. It emphasizes the importance of context in data interpretation and highlights the necessity of tailored approaches in analysis. Thus, mastering the concept of partial average is invaluable for anyone involved in data-driven fields, as it enhances the quality and relevance of insights drawn from data.

在当今世界，数据分析在各个领域的决策中发挥着至关重要的作用。统计分析中经常出现的一个关键概念是部分平均值。术语部分平均值指的是在较大数据集中某个子集的数据点的平均值。当我们想要分析特定数据段而不受整个数据集变化的影响时，这个概念特别有用。例如，在教育研究中，如果我们想评估某个班级学生的表现，我们可能会计算他们考试成绩的部分平均值，而不是查看学校所有学生的平均成绩。这允许进行更专注和相关的分析。理解如何计算部分平均值对于准确的数据解释至关重要。要找到部分平均值，首先必须确定感兴趣的数据点子集。在隔离这些数据点之后，将它们相加，然后除以该子集中的点数。这个过程有助于理解在整体平均值中可能看不到的趋势或模式。例如，如果一家公司想评估某条产品线在一个季度的销售表现，他们会单独计算该产品线的销售数字的部分平均值，而不是将其与其他无关产品混合在一起。部分平均值的重要性不仅仅体现在计算上；它还帮助做出明智的决策。在商业中，管理人员通常依赖部分平均值来评估针对特定人群的营销策略的有效性。通过分析来自特定活动的客户反馈的部分平均值，他们可以判断他们的努力是否成功，以及需要改进的地方。这种有针对性的方法确保资源得到高效和有效的分配。此外，部分平均值在学术研究中也可以发挥关键作用。研究人员在研究复杂现象时，常常需要关注特定群体或条件。例如，在一项调查新药效果的医学研究中，研究人员可能会计算某个年龄范围内患者康复时间的部分平均值。这使他们能够得出更适用于该人群的结论，而不是做出可能不适用于所有人的广泛概括。总之，部分平均值是数据分析中的一个强大工具，提供了对特定数据段的更深刻见解。通过关注子集而不是整个数据集，分析人员可以发现有意义的模式和趋势，从而为更好的决策提供信息。无论是在商业、教育还是研究中，理解和利用部分平均值都可以导致更精确的评估和结果。它强调了数据解释中上下文的重要性，并突出了分析中量身定制方法的必要性。因此，掌握部分平均值的概念对于任何参与数据驱动领域的人来说都是无价的，因为它提高了从数据中得出的见解的质量和相关性。