peakedness

简明释义

英[ˈpiːkɪdnɪs]美[ˈpiːktnəs]

n. 巅峰；尖峰；峰度

英英释义

单词用法

同义词

反义词

例句

1.These works that are entirely devoted to the Buddhist religion, represent the peakedness of Chinese stone carving art.

这些作品完全致力于佛教主题，代表了中国石刻艺术的巅峰。

2.These works that are entirely devoted to the Buddhist religion, represent the peakedness of Chinese stone carving art.

这些作品完全致力于佛教主题，代表了中国石刻艺术的巅峰。

3.The peakedness of the graph suggests a significant increase in sales during the holiday season.

图表的尖峰程度表明假日季节销售额显著增加。

4.In statistics, the peakedness of a distribution indicates how sharply it rises around the mean.

在统计学中，分布的峰度表示它在均值附近上升的陡峭程度。

5.The peakedness of the cake was achieved by carefully layering the batter.

蛋糕的高峰特征是通过精心分层面糊实现的。

6.The peakedness of the mountain made it a challenging hike for beginners.

这座山的陡峭程度使得初学者的徒步旅行变得具有挑战性。

7.The artist focused on the peakedness of the landscape to create a dramatic effect in her painting.

艺术家专注于风景的高峰特征以在她的画作中创造戏剧效果。

作文

In the world of data analysis, understanding various statistical concepts is crucial for making informed decisions. One such concept that often comes into play is peakedness, which refers to the sharpness or flatness of a probability distribution's peak. It is an essential aspect of statistics that helps analysts interpret the behavior of different datasets. The term peakedness can also be associated with kurtosis, which measures the tails and the sharpness of the distribution. A high peakedness indicates that the data has a sharp peak, suggesting that most values are concentrated around the mean, while a low peakedness implies a flatter distribution, indicating a wider spread of values.Understanding peakedness is particularly important in fields such as finance, where analysts need to assess the risks associated with various investment options. For instance, if a stock's return distribution exhibits high peakedness, it means that there is a greater likelihood of returns clustering around the average, which can be interpreted as lower risk. Conversely, a low peakedness might suggest that the stock's returns are more volatile and unpredictable, leading to higher risk. Moreover, peakedness plays a significant role in quality control processes in manufacturing. By analyzing the distribution of product measurements, quality engineers can determine whether the production process is consistent. If the measurements show high peakedness, it indicates that the products are being produced within a tight tolerance range, which is desirable for maintaining quality standards. On the other hand, a low peakedness could signal variability in the manufacturing process, prompting further investigation to identify potential issues.In educational assessments, peakedness can also be a useful metric. For example, when analyzing test scores, educators can evaluate the distribution of student performance. A high peakedness in the scores may indicate that most students performed similarly, while a low peakedness suggests a diverse range of abilities among students. This information can help educators tailor their teaching strategies to better address the needs of their students.In conclusion, the concept of peakedness is a vital tool in various fields, providing insights into the characteristics of data distributions. Whether in finance, manufacturing, or education, understanding peakedness allows professionals to make better-informed decisions based on the underlying patterns of their data. As we continue to collect and analyze vast amounts of information, grasping the nuances of statistical terms like peakedness will become increasingly important in our quest for knowledge and understanding.

在数据分析的世界中，理解各种统计概念对于做出明智的决策至关重要。其中一个经常出现的概念是peakedness，它指的是概率分布峰值的尖锐程度或平坦程度。这是统计学中的一个重要方面，帮助分析师解读不同数据集的行为。术语peakedness也可以与峰度相关联，峰度测量分布的尾部和尖锐度。高peakedness表明数据具有尖锐的峰，暗示大多数值集中在均值附近，而低peakedness则意味着分布较平坦，表明值的分布更广。理解peakedness在金融等领域尤为重要，在这些领域中，分析师需要评估与各种投资选项相关的风险。例如，如果某只股票的收益分布表现出高peakedness，这意味着收益更有可能集中在平均值附近，这可以解释为较低的风险。相反，低peakedness可能表明该股票的收益更加波动和不可预测，从而导致更高的风险。此外，peakedness在制造业的质量控制过程中也发挥着重要作用。通过分析产品测量的分布，质量工程师可以确定生产过程是否一致。如果测量显示出高peakedness，则表明产品在严格的公差范围内生产，这是维持质量标准所期望的。另一方面，低peakedness可能表示制造过程中的变异性，促使进一步调查以识别潜在问题。在教育评估中，peakedness也可以是一个有用的指标。例如，在分析考试成绩时，教育工作者可以评估学生表现的分布。成绩的高peakedness可能表明大多数学生表现相似，而低peakedness则暗示学生之间能力的多样性。这些信息可以帮助教育工作者调整他们的教学策略，更好地满足学生的需求。总之，peakedness的概念是各个领域的重要工具，为数据分布的特征提供了洞察力。无论是在金融、制造还是教育中，理解peakedness使专业人士能够根据数据的基本模式做出更明智的决策。随着我们继续收集和分析大量信息，掌握像peakedness这样的统计术语的细微差别将在我们追求知识和理解的过程中变得越来越重要。