platykurtic

简明释义

英[ˌplætɪˈkɜːtɪk]美[ˌplætɪˈkɜrtɪk]

低峰态

英英释义

单词用法

同义词

反义词

例句

1.The distribution of seedling sprout height was nearly symmetric and platykurtic, but was positively skewed for the seedling plants.

萌生苗高度的分布接近于对称的低峰分布，实生苗的偏斜度均为正值。

2.The distribution of seedling sprout height was nearly symmetric and platykurtic, but was positively skewed for the seedling plants.

萌生苗高度的分布接近于对称的低峰分布，实生苗的偏斜度均为正值。

3.In statistics, a platykurtic distribution has lighter tails compared to a normal distribution.

在统计学中，平峰态分布的尾部比正态分布更轻。

4.When analyzing the data, we noticed that it was platykurtic, suggesting a lack of extreme values.

在分析数据时，我们注意到数据是平峰态，这表明缺乏极端值。

5.The distribution of test scores was found to be platykurtic, indicating a flatter peak and more variability than a normal distribution.

测试分数的分布被发现是平峰态，这表明其峰值较平坦，变异性大于正态分布。

6.The platykurtic nature of the dataset implies that the values are more evenly spread out.

数据集的平峰态特性意味着值更均匀地分布。

7.A platykurtic curve can often be seen in real-world phenomena where outcomes are more variable.

在结果更为多变的现实现象中，常常可以看到平峰态曲线。

作文

In the field of statistics, understanding the distribution of data is crucial for effective analysis. One term that often comes up in discussions about data distributions is platykurtic, which refers to a specific type of distribution characterized by a flatter peak compared to a normal distribution. This concept is essential for statisticians and researchers who aim to interpret data accurately and make informed decisions based on their findings. To grasp the meaning of platykurtic, it is helpful to compare it with its counterpart, leptokurtic. While a leptokurtic distribution has a sharper peak and heavier tails, indicating more outliers, a platykurtic distribution demonstrates a wider spread of data points around the mean, resulting in fewer extreme values and a more uniform frequency of occurrences. The significance of identifying a platykurtic distribution lies in its implications for data interpretation. For instance, when analyzing test scores in a classroom setting, if the distribution is platykurtic, it suggests that students’ performances are relatively consistent, with most scores clustering around the average. This can help educators understand that the majority of students are performing at a similar level, which may influence teaching strategies and resource allocation. Conversely, if the distribution were leptokurtic, it would indicate that there are significant variations in student performance, prompting a need for differentiated instruction to cater to diverse learning needs.Moreover, the concept of platykurtic distributions extends beyond education into various fields such as finance, psychology, and quality control. In finance, for example, a platykurtic return distribution might suggest a stable investment with predictable returns, appealing to risk-averse investors. On the other hand, a leptokurtic return distribution could signal higher volatility and risk, attracting investors willing to take on more uncertainty for potentially higher rewards. Understanding whether a dataset is platykurtic or leptokurtic can also aid in hypothesis testing and statistical modeling. Many statistical tests assume normality in data distribution, and knowing the kurtosis helps analysts determine the appropriateness of these tests. When dealing with platykurtic data, analysts may choose different approaches or transformations to ensure accurate results, as traditional methods may not yield valid conclusions. In conclusion, the term platykurtic plays a vital role in the realm of statistics, providing insights into the nature of data distributions. By recognizing the characteristics of platykurtic distributions, researchers and analysts can make better-informed decisions, tailor their approaches to data analysis, and ultimately enhance the quality of their findings. As we continue to collect and analyze vast amounts of data in various domains, the importance of understanding concepts like platykurtic will only grow, underscoring the need for a solid foundation in statistical principles. Whether in academia, industry, or everyday life, the ability to interpret data distributions effectively can lead to more accurate conclusions and better decision-making processes.

在统计学领域，理解数据的分布对有效分析至关重要。一个常常出现在数据分布讨论中的术语是platykurtic，它指的是一种特定类型的分布，其特征是与正态分布相比具有更平坦的峰值。这个概念对于旨在准确解释数据并根据发现做出明智决策的统计学家和研究人员来说至关重要。要理解platykurtic的含义，将其与其对应词leptokurtic进行比较是有帮助的。虽然尖峰分布（leptokurtic）具有更尖锐的峰值和更重的尾部，表明存在更多的离群值，但platykurtic分布则显示出数据点围绕均值的更广泛分散，导致极端值较少，出现频率更均匀。识别platykurtic分布的重要性在于它对数据解释的影响。例如，在课堂上分析考试成绩时，如果分布是platykurtic，这表明学生的表现相对一致，大多数分数集中在平均值附近。这可以帮助教育工作者了解大多数学生的表现处于相似水平，这可能会影响教学策略和资源分配。相反，如果分布是尖峰分布（leptokurtic），则表明学生表现存在显著差异，促使需要采取差异化教学以满足不同的学习需求。此外，platykurtic分布的概念超越了教育，延伸到金融、心理学和质量控制等多个领域。例如，在金融领域，platykurtic回报分布可能表明一种稳定的投资，具有可预测的回报，吸引风险厌恶型投资者。另一方面，尖峰分布（leptokurtic）回报分布可能暗示更高的波动性和风险，吸引愿意承担更多不确定性的投资者，以期获得更高的回报。了解数据集是否为platykurtic或尖峰分布（leptokurtic）也有助于假设检验和统计建模。许多统计检验假设数据分布是正态的，而了解峰度有助于分析师确定这些检验的适用性。当处理platykurtic数据时，分析师可能会选择不同的方法或变换，以确保结果的准确性，因为传统方法可能无法得出有效的结论。总之，术语platykurtic在统计学领域发挥着至关重要的作用，为数据分布的性质提供了见解。通过识别platykurtic分布的特征，研究人员和分析师可以做出更明智的决策，量身定制他们的数据分析方法，并最终提高他们发现的质量。随着我们在各个领域继续收集和分析大量数据，理解像platykurtic这样的概念的重要性只会增加，强调了对统计原则建立坚实基础的必要性。无论是在学术界、工业界还是日常生活中，有效解释数据分布的能力都能带来更准确的结论和更好的决策过程。