bias; deviation

简明释义

偏向

英英释义

例句

1.We need to address the deviation; 偏差 in the results to ensure accuracy.

我们需要解决结果中的偏差; 偏差以确保准确性。

2.The deviation; 偏差 from the expected outcome raised concerns among the researchers.

与预期结果的偏差; 偏差引起了研究人员的关注。

3.The study showed a significant bias; 偏见 in the data collection process.

研究显示数据收集过程中存在显著的偏见; 偏见。

4.It's essential to minimize any bias; 偏见 in scientific research.

在科学研究中，尽量减少任何偏见; 偏见是至关重要的。

5.Her personal bias; 偏见 affected her judgment during the interview.

她的个人偏见; 偏见影响了她在面试中的判断。

作文

In the realm of research and data analysis, understanding concepts such as bias（偏见） and deviation（偏差） is crucial for drawing accurate conclusions. Bias refers to a systematic error that can lead to incorrect results or interpretations. It can stem from various sources, such as the selection of participants, the way data is collected, or even the personal beliefs of the researcher. For instance, if a survey is conducted only among a specific demographic group, the results may not be representative of the larger population, leading to a bias in the findings.On the other hand, deviation is a statistical term that describes the extent to which individual data points differ from the mean or expected value. While some degree of deviation is normal in any dataset, excessive deviation can indicate issues with the data collection process or the presence of outliers. Understanding both bias and deviation is vital for researchers who aim to present reliable and valid results.To illustrate these concepts, consider a study investigating the effectiveness of a new educational program. If the researchers choose to only include students from high-performing schools, their results may show a significant improvement in academic performance. However, this would likely reflect a bias in the sample selection, as it does not account for students in underperforming schools who may benefit differently from the program.Furthermore, if the researchers fail to account for varying levels of prior knowledge among students, the deviation in performance outcomes could be misleading. A wide range of scores might suggest that the program is ineffective, but this deviation could simply be due to differences in student backgrounds rather than the program itself.In conclusion, both bias and deviation play significant roles in research and data analysis. By recognizing and addressing potential bias, researchers can enhance the validity of their studies. Additionally, understanding deviation helps in interpreting data accurately, allowing for more informed decisions based on the findings. Researchers must remain vigilant about these factors to ensure their work contributes meaningfully to their respective fields. Only through careful consideration of bias and deviation can we hope to achieve genuine insights and advancements in knowledge.

在研究和数据分析领域，理解诸如偏见（bias）和偏差（deviation）等概念对于得出准确的结论至关重要。偏见是指一种系统性的错误，这种错误可能导致结果或解释不正确。它可以源于多种因素，例如参与者的选择、数据收集的方式，甚至研究者的个人信念。例如，如果一项调查仅在特定的人口群体中进行，那么结果可能无法代表更大的人口，从而导致研究结果中的偏见。另一方面，偏差是一个统计术语，用来描述个别数据点与均值或预期值之间的差异程度。虽然在任何数据集中都有一定程度的偏差是正常的，但过度的偏差可能表明数据收集过程存在问题或存在异常值。理解偏见和偏差对那些希望呈现可靠和有效结果的研究人员至关重要。为了说明这些概念，考虑一项研究，调查新教育项目的有效性。如果研究者选择仅包括高表现学校的学生，他们的结果可能显示学业成绩显著提高。然而，这很可能反映了样本选择中的偏见，因为它没有考虑到来自表现不佳学校的学生，他们可能以不同的方式受益于该项目。此外，如果研究者未能考虑学生之间的先前知识水平差异，成绩结果的偏差可能会产生误导。广泛的分数范围可能表明该项目无效，但这种偏差可能仅仅是由于学生背景的差异，而不是项目本身。总之，偏见和偏差在研究和数据分析中扮演着重要角色。通过识别和解决潜在的偏见，研究人员可以提高研究的有效性。此外，理解偏差有助于准确解读数据，使基于研究结果的决策更加明智。研究人员必须对这些因素保持警惕，以确保他们的工作为各自的领域做出有意义的贡献。只有通过仔细考虑偏见和偏差，我们才能希望获得真正的洞察和知识的进步。