standard deviation

简明释义

均方根偏差

英英释义

例句

1.In finance, a high standard deviation 标准差 of investment returns suggests higher risk.

在金融领域，高标准差 标准差 的投资回报率意味着更高的风险。

2.The standard deviation 标准差 of the test scores indicates how much the scores vary from the average.

考试分数的标准差 标准差 显示了分数与平均值的偏差程度。

3.A low standard deviation 标准差 means that the data points are close to the mean.

低标准差 标准差 意味着数据点接近均值。

4.The standard deviation 标准差 helps identify outliers in a dataset.

标准差 标准差 有助于识别数据集中的异常值。

5.To understand the variability in data, we often calculate the standard deviation 标准差.

为了理解数据的变异性，我们通常计算标准差 标准差。

作文

In the realm of statistics, one of the most crucial concepts is the measure of variability, which helps us understand how data points differ from the mean. Among various statistical measures, the standard deviation plays a vital role. The standard deviation is defined as a statistic that quantifies the amount of variation or dispersion in a set of values. A low standard deviation indicates that the data points tend to be close to the mean, while a high standard deviation suggests that the data points are spread out over a wider range of values. To illustrate this concept, consider two different sets of test scores from two classes. Class A has scores of 85, 87, 86, 88, and 84, while Class B has scores of 70, 90, 60, 100, and 80. Despite both classes having the same average score of 86, the standard deviation for Class A will be significantly lower than that of Class B. This is because the scores in Class A are closely clustered around the mean, whereas Class B's scores are more dispersed. Understanding the standard deviation is essential not only in academic settings but also in real-world applications. For instance, investors use the standard deviation to assess the risk associated with a particular investment. A higher standard deviation in stock prices may indicate greater volatility, suggesting that the investment carries a higher risk. Conversely, a lower standard deviation may signal a more stable investment with predictable returns.Moreover, the standard deviation is widely used in quality control processes within manufacturing industries. By monitoring the standard deviation of product measurements, manufacturers can ensure that their products meet quality standards. If the standard deviation exceeds a certain threshold, it could indicate a problem in the production process that needs to be addressed. In educational assessments, the standard deviation provides valuable insights into student performance. Educators can analyze the standard deviation of exam scores to determine whether students are performing consistently or if there are significant discrepancies in their understanding of the material. A high standard deviation may prompt educators to review their teaching methods or provide additional support to struggling students.Furthermore, in the field of psychology, researchers often use the standard deviation to interpret data from surveys and experiments. Understanding the standard deviation allows psychologists to draw conclusions about the variability in responses and to identify patterns that may not be immediately apparent from the mean alone. In conclusion, the standard deviation is a fundamental statistical tool that provides insight into the variability of data. Its applications span across various fields, including finance, education, manufacturing, and psychology. By grasping the significance of the standard deviation, individuals can make informed decisions based on a deeper understanding of data variability. As we continue to navigate a data-driven world, the importance of understanding the standard deviation cannot be overstated. It empowers us to analyze information critically and to draw meaningful conclusions from the data at hand.

在统计学领域，最重要的概念之一是变异度的测量，这有助于我们理解数据点与均值之间的差异。在各种统计测量中，标准差扮演着至关重要的角色。标准差被定义为量化一组值的变异或离散程度的统计量。较低的标准差表明数据点倾向于接近均值，而较高的标准差则表明数据点在更广泛的值范围内分布。为了说明这一概念，考虑两个不同班级的考试成绩。A班的成绩为85、87、86、88和84，而B班的成绩为70、90、60、100和80。尽管两个班级的平均分都是86，但A班的标准差将显著低于B班的标准差。这是因为A班的成绩紧密聚集在均值附近，而B班的成绩则更为分散。理解标准差不仅在学术环境中至关重要，而且在现实世界的应用中也同样重要。例如，投资者使用标准差来评估特定投资的风险。股票价格的较高标准差可能表明更大的波动性，暗示该投资具有更高的风险。相反，较低的标准差可能表示一个更稳定的投资，具有可预测的回报。此外，标准差在制造业的质量控制过程中被广泛使用。通过监测产品测量的标准差，制造商可以确保其产品符合质量标准。如果标准差超过某个阈值，这可能表明生产过程中存在需要解决的问题。在教育评估中，标准差提供了有关学生表现的宝贵见解。教育工作者可以分析考试成绩的标准差，以确定学生表现是否一致，或者他们对材料的理解是否存在显著差异。较高的标准差可能促使教育工作者审查其教学方法或为困难的学生提供额外支持。此外，在心理学领域，研究人员经常使用标准差来解释调查和实验的数据。理解标准差使心理学家能够得出关于反应变异性的结论，并识别可能不立即从均值中显现出的模式。总之，标准差是一个基本的统计工具，提供了对数据变异性的洞察。它的应用跨越多个领域，包括金融、教育、制造和心理学。通过掌握标准差的意义，个人可以基于对数据变异性的更深入理解做出明智的决策。随着我们继续在数据驱动的世界中航行，理解标准差的重要性不容小觑。它使我们能够批判性地分析信息，并从手头的数据中得出有意义的结论。