uncorrelated

简明释义

英[ˌʌnˈkɒrɪleɪtɪd]美[ʌnˈkɒrɪleɪtɪd]

adj. 不相关的

英英释义

单词用法

同义词

反义词

例句

1.When uncertainty was from the liquidation value, debt was uncorrelated with pricing decision-making.

而当清算价值不确定时，债务不影响企业产品市场的价格决策。

2.Using the principle of the reference signal being uncorrelated to the measured signal, the latter could be extracted easily.

利用噪声信号与参考信号不相关的原理，有效地提取微弱被测信号。

3.There are two types of subqueries, uncorrelated and correlated.

有两种类型的子查询： 不相关的和相关的。

4.Two identical chaotic systems starting from almost identical initial states, end in completely uncorrelated trajectories.

两个同源的混沌系统从几乎完全相同的初始状态开始演变，最后划出两个完全不相关的轨迹。

5.Correlated assets move together-they're affected in similar ways by the same market forces-while uncorrelated assets move in different directions.

相关资产一起变动——它们受相同市场力量影响——而不相关的资产则变动方向不同。

6.Undergraduates' Emotional intelligence is uncorrelated with their academic achievement.

大学生情绪智力和学业成绩之间不存在相关。

7.Secondly, two efficient methods are suggested without pairing match problems when the signals are uncorrelated.

其次，针对非相关信号环境提出了两种自动配对的有效联合估计方法。

8.In finance, an uncorrelated asset can help diversify a portfolio and reduce risk.

在金融中，不相关的资产可以帮助分散投资组合并降低风险。

9.The stock prices of these two companies are uncorrelated, which means they do not move together.

这两家公司的股票价格是不相关的，这意味着它们不会一起波动。

10.The two variables in the study were found to be uncorrelated, indicating that changes in one did not affect the other.

研究中发现这两个变量是不相关的，表明一个的变化并不影响另一个。

11.The experiment demonstrated that the results were uncorrelated with the initial hypotheses.

实验表明结果与初始假设是不相关的。

12.The research showed that the temperature and the number of ice creams sold were uncorrelated on rainy days.

研究表明，在雨天，温度和冰淇淋销售数量是不相关的。

作文

In the realm of statistics and data analysis, the concept of being uncorrelated plays a crucial role in understanding the relationships between different variables. When we say that two variables are uncorrelated, we mean that there is no predictable relationship between them; changes in one variable do not systematically lead to changes in the other. This characteristic can be particularly important in fields such as economics, finance, and social sciences, where researchers often seek to identify patterns or correlations among various factors.For instance, consider the relationship between the number of ice creams sold and the number of people wearing sunglasses on a summer day. While both may increase as the temperature rises, they are uncorrelated in the sense that one does not cause or predict the other. The increase in ice cream sales is driven by the heat, while the sale of sunglasses is influenced by fashion trends, personal preferences, and other factors. Thus, although they may appear related due to external conditions, their lack of correlation highlights the importance of examining underlying causes rather than assuming a direct link between two variables.Understanding uncorrelated variables is also vital in financial markets. Investors often analyze the performance of different assets to build a diversified portfolio. By including assets that are uncorrelated with each other, investors can reduce risk and improve potential returns. For example, stocks and bonds may exhibit uncorrelated behavior during certain market conditions, meaning that when stock prices fall, bond prices may remain stable or even rise. This uncorrelated nature allows investors to mitigate losses and achieve more stable overall performance.Moreover, the concept of uncorrelated variables extends beyond mere statistics and finance; it also has implications in machine learning and artificial intelligence. In these fields, algorithms are designed to recognize patterns and make predictions based on input data. When training models, it is advantageous to include features that are uncorrelated with one another. This ensures that the model learns from diverse information without redundancy, leading to better accuracy and efficiency in predictions.On a broader scale, recognizing uncorrelated phenomena can help us make more informed decisions in our daily lives. For example, understanding that one's mood might be uncorrelated with external circumstances, such as the weather or the day of the week, can empower individuals to take control of their emotional well-being. By focusing on internal factors and personal choices rather than attributing feelings to external events, people can cultivate a more resilient mindset.In conclusion, the concept of uncorrelated variables is fundamental across various disciplines. Whether in statistics, finance, machine learning, or personal development, recognizing the absence of correlation can lead to deeper insights and more effective strategies. As we continue to explore complex systems and relationships, understanding what is uncorrelated helps us navigate through uncertainty and make better-informed decisions in both our professional and personal lives.

在统计学和数据分析领域，uncorrelated（不相关）这一概念在理解不同变量之间的关系时起着至关重要的作用。当我们说两个变量是uncorrelated时，我们的意思是它们之间没有可预测的关系；一个变量的变化不会系统性地导致另一个变量的变化。这一特征在经济学、金融学和社会科学等领域尤为重要，因为研究人员常常试图识别各种因素之间的模式或相关性。例如，考虑在夏天销售的冰淇淋数量与佩戴太阳镜的人数之间的关系。虽然这两者都可能随着温度的升高而增加，但它们在某种意义上是uncorrelated的，因为一个的变化并不导致或预测另一个的变化。冰淇淋销量的增加是由于炎热天气的影响，而太阳镜的销售则受到时尚潮流、个人偏好和其他因素的影响。因此，尽管由于外部条件它们看起来相关，但缺乏相关性突显了研究潜在原因的重要性，而不是假设两个变量之间存在直接联系。理解uncorrelated变量在金融市场中同样至关重要。投资者通常会分析不同资产的表现，以建立多元化投资组合。通过包含彼此uncorrelated的资产，投资者可以降低风险，提高潜在回报。例如，在某些市场条件下，股票和债券可能表现出uncorrelated的行为，这意味着当股票价格下跌时，债券价格可能保持稳定甚至上涨。这种uncorrelated的特性使得投资者能够减轻损失，实现更稳定的整体表现。此外，uncorrelated变量的概念超越了单纯的统计学和金融学；它在机器学习和人工智能领域也有重要意义。在这些领域中，算法旨在基于输入数据识别模式并进行预测。在训练模型时，包含彼此uncorrelated的特征是有利的。这确保模型从多样的信息中学习，而没有冗余，从而提高预测的准确性和效率。在更广泛的层面上，认识到uncorrelated现象可以帮助我们在日常生活中做出更明智的决策。例如，理解一个人的情绪可能与外部环境（如天气或星期几）是uncorrelated的，可以使个人掌控自己的情感健康。通过关注内部因素和个人选择，而不是将情感归因于外部事件，人们可以培养出更强韧的心态。总之，uncorrelated变量的概念在各个学科中都是基础性的。无论是在统计学、金融学、机器学习还是个人发展中，认识到缺乏相关性都可以带来更深刻的见解和更有效的策略。随着我们继续探索复杂的系统和关系，理解什么是uncorrelated有助于我们在不确定性中导航，并在职业和个人生活中做出更明智的决策。