degree of dispersion

简明释义

分散度

英英释义

例句

1.The degree of dispersion in the data indicates how spread out the values are from the mean.

数据中的离散程度表明值与均值的偏离程度。

2.The degree of dispersion among the test scores showed significant differences in student performance.

考试成绩的离散程度显示出学生表现的显著差异。

3.A low degree of dispersion suggests that the data points are closely clustered together.

低离散程度表明数据点紧密聚集在一起。

4.Researchers measured the degree of dispersion in the population's income levels for their study.

研究人员测量了该人群收入水平的离散程度以进行研究。

5.In finance, a higher degree of dispersion can signal increased risk in investment portfolios.

在金融中，较高的离散程度可能表示投资组合的风险增加。

作文

In the field of statistics, understanding the concept of degree of dispersion is crucial for interpreting data accurately. The degree of dispersion refers to the extent to which data points in a dataset vary from the average or mean value. This variability can provide insights into the reliability and consistency of the data, as well as help identify any outliers that may skew the results. For instance, if we consider the test scores of a group of students, the degree of dispersion will indicate how closely the scores cluster around the average score. A low degree of dispersion suggests that most students scored similarly, while a high degree of dispersion indicates a wide range of scores, reflecting diverse levels of understanding among the students.To illustrate this further, let's take an example of two classrooms. In Classroom A, the students scored between 85 and 95 on their mathematics test, resulting in a mean score of 90. In Classroom B, however, the scores ranged from 60 to 100, with a mean score also at 90. While both classrooms have the same average score, the degree of dispersion in Classroom B is much higher. This means that while the average performance appears similar, the actual performance levels are more varied in Classroom B, indicating that some students may be struggling significantly compared to others.The degree of dispersion can be measured using various statistical tools, such as the range, variance, and standard deviation. The range is the simplest measure, calculated by subtracting the lowest score from the highest score. Variance and standard deviation are more advanced measures that take into account how each data point differs from the mean. A higher variance or standard deviation signifies a greater degree of dispersion, suggesting that the data points are spread out over a wider range.Understanding the degree of dispersion is not only important in educational settings but also in various fields such as finance, healthcare, and social sciences. For example, in finance, investors analyze the degree of dispersion of stock returns to assess risk. A stock with a high degree of dispersion implies greater volatility, which could lead to higher potential returns but also increased risk.Moreover, in healthcare, researchers might study the degree of dispersion in patient recovery times after a specific treatment. A lower degree of dispersion in recovery times would suggest that the treatment is effective and consistent across patients, while a higher degree of dispersion might indicate varying responses to the treatment, prompting further investigation into patient-specific factors.In conclusion, the degree of dispersion is a fundamental concept that plays a pivotal role in data analysis across different domains. By examining the degree of dispersion, researchers and analysts can gain deeper insights into the variability and reliability of their data, leading to more informed decisions. Whether in education, finance, or healthcare, recognizing and understanding the degree of dispersion enables us to interpret data more effectively and make better predictions about future trends.

在统计学领域，理解“离散程度”这一概念对于准确解读数据至关重要。“离散程度”指的是数据集中数据点相对于平均值或均值的变化程度。这种变异性可以提供关于数据可靠性和一致性的见解，同时帮助识别可能扭曲结果的异常值。例如，如果我们考虑一组学生的考试成绩，“离散程度”将表明大多数学生的成绩如何围绕平均成绩聚集。较低的“离散程度”表明大多数学生的成绩相似，而较高的“离散程度”则表示成绩范围广泛，反映出学生之间理解水平的多样性。为了进一步说明这一点，我们以两个教室为例。在A教室，学生的数学考试成绩在85到95之间，平均分为90。然而，在B教室，成绩范围从60到100，平均分同样为90。虽然两个教室的平均分相同，但B教室的“离散程度”要高得多。这意味着，尽管平均表现看似相似，但B教室的实际表现水平更加多样化，表明一些学生的理解水平明显低于其他学生。“离散程度”可以通过多种统计工具来测量，例如范围、方差和标准差。范围是最简单的度量，通过将最低分数减去最高分数来计算。方差和标准差是更高级的度量，它们考虑了每个数据点与均值的差异。较高的方差或标准差意味着更大的“离散程度”，表明数据点分布在更广泛的范围内。理解“离散程度”不仅在教育领域重要，在金融、医疗保健和社会科学等多个领域也同样重要。例如，在金融领域，投资者分析股票收益的“离散程度”以评估风险。具有高“离散程度”的股票意味着更大的波动性，这可能导致更高的潜在回报，但同时也增加了风险。此外，在医疗保健中，研究人员可能会研究特定治疗后患者恢复时间的“离散程度”。较低的“离散程度”表明该治疗在患者中的效果一致，而较高的“离散程度”可能表明对治疗的反应存在差异，从而促使对患者特定因素的进一步调查。总之，“离散程度”是一个基本概念，在不同领域的数据分析中发挥着关键作用。通过考察“离散程度”，研究人员和分析师能够深入了解数据的变异性和可靠性，从而做出更明智的决策。无论是在教育、金融还是医疗保健领域，认识和理解“离散程度”使我们能够更有效地解读数据，并更好地预测未来趋势。