bimodality

简明释义

英[ˌbaɪˈmoʊˌdæl.ɪ.ti]美[ˌbaɪˈmoʊˌdæl.ɪ.ti]

n. 双峰性

英英释义

单词用法

同义词

反义词

例句

1.This will help to overcome problems of apparent bimodality caused by the presence of many below-detection-limit values in a data set.

这将有助于克服因数据组中有大量低于捡出限的数值而出双模态性的问题。

2.This will help to overcome problems of apparent bimodality caused by the presence of many below-detection-limit values in a data set.

这将有助于克服因数据组中有大量低于捡出限的数值而出双模态性的问题。

3.The data showed a clear bimodality in the distribution of test scores, indicating two distinct groups of students.

数据在考试分数的分布中显示出明显的双峰性，表明有两个不同的学生群体。

4.In the survey results, bimodality was evident, with respondents favoring either extreme opinions.

在调查结果中，显现出双峰性，受访者偏向于极端的观点。

5.Researchers noted a bimodality in the age distribution of participants in the study, with peaks in both younger and older age groups.

研究人员注意到研究参与者的年龄分布呈现出双峰性，在年轻和年长的年龄组都有高峰。

6.The bimodality of the species' population in different habitats indicates varying survival strategies.

物种在不同栖息地中的双峰性人口表明了不同的生存策略。

7.The bimodality of the income levels in the city suggests that there are significant economic divides among its residents.

该城市收入水平的双峰性表明居民之间存在显著的经济差距。

作文

In the field of statistics, the concept of bimodality refers to the presence of two distinct modes or peaks in a frequency distribution. This phenomenon can be observed in various datasets, where values cluster around two different points rather than forming a single peak. Understanding bimodality is crucial for data analysis, as it can reveal underlying patterns that may not be immediately apparent when examining the data as a whole.For instance, consider a scenario where we are analyzing the test scores of a class. If the scores show a bimodal distribution, we might find that there are two groups of students: one group that performed exceptionally well and another that struggled significantly. This insight can lead educators to tailor their teaching strategies to better address the needs of both groups, providing additional support to those who need it while also challenging the high achievers.Moreover, bimodality can be observed in various real-world applications beyond education. In economics, for example, income distribution often exhibits bimodal characteristics, with one mode representing the lower-income bracket and another representing the higher-income bracket. This can indicate significant disparities within a population and prompt policymakers to implement measures aimed at reducing inequality.In the realm of health and medicine, researchers might encounter bimodality when studying the effects of a particular drug on different demographics. If a clinical trial shows two distinct responses to the medication—one group experiencing beneficial effects while another suffers adverse reactions—this finding would be critical for developing personalized treatment plans. It highlights the importance of recognizing that a one-size-fits-all approach may not be effective, as individual responses can vary widely.Furthermore, the identification of bimodality can play a significant role in marketing and consumer behavior analysis. Companies often analyze purchasing patterns to determine how consumers behave under different conditions. If data reveals a bimodal distribution of purchases—such as consumers who buy luxury items versus those who prefer budget-friendly options—marketers can develop targeted campaigns that cater to each segment, maximizing their outreach and effectiveness.In conclusion, the concept of bimodality is an essential aspect of data analysis that can provide valuable insights across various disciplines. Recognizing and understanding bimodality allows researchers, educators, policymakers, and marketers to make informed decisions based on the underlying patterns present in their data. By acknowledging the existence of two distinct modes, we can better address the complexities of the world around us, leading to more effective solutions and strategies tailored to the diverse needs of different groups. As we continue to collect and analyze data in our increasingly complex society, the significance of bimodality will undoubtedly grow, making it an important concept for future study and application.

在统计学领域，概念bimodality指的是频率分布中存在两个不同的众数或峰值。这种现象可以在各种数据集中观察到，其中数值围绕两个不同的点聚集，而不是形成单一的峰值。理解bimodality对于数据分析至关重要，因为它可以揭示潜在的模式，这些模式在整体上检查数据时可能并不明显。例如，考虑一个分析班级测试成绩的场景。如果成绩呈现出bimodal分布，我们可能会发现有两组学生：一组表现优秀，另一组则表现不佳。这一见解可以促使教育工作者量身定制教学策略，以更好地满足这两组的需求，为需要额外支持的学生提供帮助，同时也挑战高成就者。此外，bimodality可以在教育之外的各种现实应用中观察到。在经济学中，例如，收入分配通常表现出bimodal特征，一个众数代表低收入群体，另一个代表高收入群体。这可能表明人口内部存在显著差异，并促使政策制定者实施旨在减少不平等的措施。在健康和医学领域，研究人员在研究某种药物对不同人群的影响时，可能会遇到bimodality。如果临床试验显示对药物的反应存在两个截然不同的结果——一组体验到有益效果，而另一组则遭受不良反应——这一发现对于制定个性化治疗计划至关重要。它强调了认识到一刀切的方法可能无效的重要性，因为个体反应可能差异很大。此外，识别bimodality在市场营销和消费者行为分析中也发挥着重要作用。公司经常分析购买模式，以确定消费者在不同条件下的行为。如果数据揭示出购买的bimodal分布——例如，消费者购买奢侈品与偏好预算友好型选项——营销人员可以制定针对每个细分市场的有针对性的活动，从而最大化其覆盖面和有效性。总之，bimodality的概念是数据分析的一个基本方面，可以在各个学科中提供有价值的见解。识别和理解bimodality使研究人员、教育工作者、政策制定者和营销人员能够根据数据中存在的潜在模式做出明智的决定。通过承认存在两个不同的众数，我们可以更好地解决我们周围世界的复杂性，从而导致更有效的解决方案和策略，满足不同群体的多样化需求。随着我们在日益复杂的社会中继续收集和分析数据，bimodality的重要性无疑会增长，使其成为未来研究和应用的重要概念。