skewed

简明释义

英[skjuːd]美[skjuːd]

adj. 歪斜的；曲解的

英英释义

单词用法

同义词

反义词

例句

1.The car had ended up skewed across the road.

汽车最终斜着停在公路上。

2.Is the data skewed?

数据是否倾斜？

3.And that distribution is skewed either low or high depending on the temperature.

这个分布的倾斜程度，依赖于温度的高低。

4.The ball skewed off at a right angle.

球呈直角偏离弹了出去。

5.People said the dairy industry and the meat industry were especially effective at lobbying and that gave you a skewed version of what to eat.

人们说乳制品行业和肉类行业在游说方面特别有效，并给了你一个歪曲版本的饮食建议。

6.Because science never stops, neither can this most culturally-skewed of debates.

因为科学永远不会停止，这场更受文化所左右的辩论也就永远不会停止。

7.The data presented in the report is skewed due to sampling bias.

报告中呈现的数据由于抽样偏差而扭曲。

8.Her perception of the event was skewed by her previous experiences.

她对事件的看法因之前的经历而偏颇。

9.The graph shows a skewed distribution of income among different demographics.

图表显示了不同人口统计之间收入的歪斜分布。

10.His argument was skewed towards one side of the debate.

他的论点在辩论中是偏向一方的。

11.The survey results were skewed because most respondents were from urban areas.

调查结果因大多数受访者来自城市地区而被扭曲。

作文

In today's world, data plays a crucial role in decision-making processes across various fields, including business, healthcare, and education. However, the interpretation of data can often be misleading if it is not analyzed correctly. One common issue that arises in data analysis is when the results are skewed (偏斜的), leading to incorrect conclusions and potentially harmful decisions. Understanding how data can be skewed (偏斜的) is essential for anyone involved in data interpretation. To begin with, it is important to recognize what we mean by skewed (偏斜的) data. In statistics, skewness refers to the degree of asymmetry observed in a distribution. A normal distribution has a symmetrical bell shape, but when data is skewed (偏斜的), it can lean towards one side, either left or right. This can significantly impact the mean, median, and mode of the data set, resulting in a misrepresentation of the actual situation. For instance, consider a company that is analyzing employee salaries. If most employees earn between $40,000 and $60,000, but there are a few executives earning millions, the average salary could be skewed (偏斜的) upwards. This would give a false impression of the typical salary within the company. Instead, the median salary would provide a more accurate representation, as it is less affected by extreme values. Therefore, recognizing skewed (偏斜的) data is vital for making informed decisions based on accurate information. Moreover, skewed (偏斜的) data can arise from various sources, including sampling errors, biased surveys, or even the way questions are framed. For example, if a survey about customer satisfaction only includes responses from loyal customers, the results will likely be skewed (偏斜的) towards positive feedback, ignoring the opinions of dissatisfied customers. This can lead businesses to overlook critical areas for improvement, ultimately affecting their success. In addition to business applications, skewed (偏斜的) data can have significant implications in public health. During the COVID-19 pandemic, for example, data reporting varied widely between different regions and demographics. If certain populations were underrepresented in testing or vaccination data, the overall statistics could be skewed (偏斜的), leading to misguided public health policies. It is crucial for health officials to ensure that data collection methods are comprehensive and unbiased to avoid skewed (偏斜的) results that could endanger lives. Furthermore, understanding the concept of skewed (偏斜的) data is not only relevant for professionals but also for individuals who consume information daily. In an age where misinformation can spread rapidly, being able to critically assess data sources and their potential biases is essential. For example, news articles often present statistics without proper context, which can lead to a skewed (偏斜的) understanding of issues. By questioning the validity of the data presented and considering its distribution, individuals can form more balanced opinions. In conclusion, the concept of skewed (偏斜的) data is a fundamental aspect of data analysis that must be understood to make informed decisions. Whether in business, healthcare, or everyday life, recognizing when data is skewed (偏斜的) allows for a more accurate interpretation of information. As we continue to rely on data-driven insights, fostering a critical mindset towards data interpretation will empower us to navigate the complexities of the modern world effectively.

在当今世界，数据在商业、医疗和教育等各个领域的决策过程中发挥着至关重要的作用。然而，如果数据没有被正确分析，其解释往往会产生误导。当数据分析中出现的问题之一是结果被skewed（偏斜的），这会导致错误的结论和潜在的有害决策。理解数据如何被skewed（偏斜的）对于任何参与数据解释的人来说都是至关重要的。 首先，重要的是要认识到我们所说的skewed（偏斜的）数据是什么意思。在统计学中，偏斜度指的是分布观察到的非对称程度。正态分布具有对称的钟形曲线，但当数据被skewed（偏斜的）时，它可能向一侧倾斜，无论是左侧还是右侧。这会显著影响数据集的均值、中位数和众数，从而导致实际情况的错误表示。 例如，考虑一家正在分析员工薪资的公司。如果大多数员工的薪资在$40,000到$60,000之间，但有几个高管的薪资为数百万美元，那么平均薪资可能会被skewed（偏斜的）向上。这将给人一种错误的印象，即公司内的典型薪资。相反，中位数薪资将提供更准确的表示，因为它不易受到极端值的影响。因此，识别skewed（偏斜的）数据对于基于准确的信息做出明智的决定至关重要。 此外，skewed（偏斜的）数据可能来自多种来源，包括抽样误差、偏见调查，甚至问题的表述方式。例如，如果一项关于客户满意度的调查仅包含忠实客户的反馈，那么结果可能会倾向于积极反馈，从而忽视不满意客户的意见。这可能导致企业忽视关键的改进领域，最终影响其成功。 除了商业应用之外，skewed（偏斜的）数据在公共卫生方面也可能产生重大影响。例如，在COVID-19大流行期间，不同地区和人群之间的数据报告差异很大。如果某些人群在检测或疫苗接种数据中被低估，那么整体统计数据可能会被skewed（偏斜的），导致公共卫生政策的误导。卫生官员必须确保数据收集方法全面且无偏，以避免可能危及生命的skewed（偏斜的）结果。 此外，理解skewed（偏斜的）数据的概念不仅与专业人士相关，也与每天消费信息的个人相关。在一个错误信息可以迅速传播的时代，能够批判性地评估数据来源及其潜在偏见至关重要。例如，新闻文章经常在没有适当背景的情况下呈现统计数据，这可能导致对问题的skewed（偏斜的）理解。通过质疑所呈现数据的有效性并考虑其分布，个人可以形成更平衡的观点。 总之，skewed（偏斜的）数据的概念是数据分析的一个基本方面，必须理解以做出明智的决策。无论是在商业、医疗还是日常生活中，识别数据何时被skewed（偏斜的）都能让我们更准确地解读信息。随着我们继续依赖数据驱动的洞察，培养对数据解释的批判性思维将使我们能够有效地应对现代世界的复杂性。