numerical concentration

简明释义

数值浓度

英英释义

例句

1.The numerical concentration 数值浓度 of bacteria in the sample was alarming and required immediate action.

样本中细菌的数值浓度 numerical concentration令人担忧，需要立即采取行动。

2.Understanding the numerical concentration 数值浓度 of nutrients is essential for effective agricultural practices.

了解养分的数值浓度 numerical concentration对有效的农业实践至关重要。

3.The report highlighted the numerical concentration 数值浓度 of pollutants in the river, showing a significant increase over the past decade.

报告强调了河流中污染物的数值浓度 numerical concentration，显示出在过去十年中显著增加。

4.In the chemistry lab, we measured the numerical concentration 数值浓度 of the solution to ensure accurate results.

在化学实验室，我们测量了溶液的数值浓度 numerical concentration以确保结果的准确性。

5.The study focused on the numerical concentration 数值浓度 of heavy metals in urban soils.

研究集中在城市土壤中重金属的数值浓度 numerical concentration。

作文

In the field of data analysis and statistics, the term numerical concentration refers to the distribution of numerical values within a dataset. This concept is crucial for understanding how data points are clustered around a central value, such as the mean or median. When we talk about numerical concentration in a given dataset, we often analyze how tightly the data points are packed together, which can provide insights into the variability and overall structure of the data. For instance, a dataset with high numerical concentration indicates that most of the values are close to each other, whereas a dataset with low numerical concentration shows a wider spread of values.To illustrate this, consider a classroom where students' test scores are analyzed. If most students score between 85 and 90, we would say there is a high numerical concentration around those scores. This would suggest that the teaching methods were effective for most students, leading to similar performance levels. Conversely, if the scores range from 50 to 100 with no clear clustering, the numerical concentration is low, indicating a disparity in student understanding or preparation.Understanding numerical concentration is also essential in fields like finance and economics. For example, when examining income distributions within a population, a high numerical concentration in the upper income brackets suggests economic inequality, while a more uniform distribution indicates a more equitable income spread. Analysts often use measures such as the Gini coefficient or standard deviation to quantify numerical concentration and assess economic health.Moreover, in scientific research, numerical concentration can be applied to various phenomena. In environmental studies, researchers might measure pollutant concentrations in different areas. A high numerical concentration of pollutants in a specific region could indicate an environmental issue that requires immediate attention. On the other hand, a low numerical concentration of pollutants suggests that the area is relatively clean, which can be encouraging news for local communities.In conclusion, numerical concentration is a fundamental concept that plays a significant role across multiple disciplines. It helps researchers, analysts, and decision-makers understand the distribution and implications of data. By analyzing numerical concentration, we can gain deeper insights into trends, patterns, and anomalies within datasets, allowing for informed decisions based on statistical evidence. As we continue to collect and analyze vast amounts of data in our increasingly data-driven world, mastering the concept of numerical concentration will remain vital for effective interpretation and application of information.

在数据分析和统计学领域，术语numerical concentration指的是数据集中数值的分布。这个概念对于理解数据点是如何围绕中心值（如均值或中位数）聚集至关重要。当我们谈论某个数据集中的numerical concentration时，我们通常会分析数据点的紧密程度，这可以提供关于数据变异性和总体结构的见解。例如，一个具有高numerical concentration的数据集表明大多数值彼此接近，而一个具有低numerical concentration的数据集则显示出更广泛的值分布。为了说明这一点，考虑一个课堂上学生考试成绩的分析。如果大多数学生的得分在85到90之间，我们可以说这些得分周围的numerical concentration很高。这表明教学方法对大多数学生有效，导致了相似的表现水平。相反，如果得分范围从50到100没有明显的聚集，那么numerical concentration就很低，表明学生的理解或准备存在差异。理解numerical concentration在金融和经济等领域也至关重要。例如，在研究人口收入分布时，较高的numerical concentration在高收入阶层表明经济不平等，而更均匀的分布则表明收入分配更为公平。分析师通常使用基尼系数或标准差等指标来量化numerical concentration并评估经济健康状况。此外，在科学研究中，numerical concentration可以应用于各种现象。在环境研究中，研究人员可能会测量不同区域的污染物浓度。特定区域中污染物的高numerical concentration可能表明需要立即关注的环境问题。另一方面，污染物的低numerical concentration则表明该地区相对干净，这对当地社区来说可能是好消息。总之，numerical concentration是一个基本概念，在多个学科中发挥着重要作用。它帮助研究人员、分析师和决策者理解数据的分布及其影响。通过分析numerical concentration，我们可以深入了解数据集中的趋势、模式和异常，从而在统计证据的基础上做出明智的决策。随着我们在日益数据驱动的世界中继续收集和分析大量数据，掌握numerical concentration的概念将对有效解读和应用信息至关重要。