variances
简明释义
英[ˈveə.ri.ənsɪz]美[ˈvɛr.i.ənsɪz]
n. 差异；变化幅度；差额（variance 的复数）
英英释义
不同、偏离或不一致的状态。 | |
A measure of the dispersion of a set of values, indicating how much the values differ from the mean. | 一组值的离散程度的度量，指示这些值与均值的差异程度。 |
单词用法
方差分析；差异分析 | |
方差分析 |
同义词
反义词
| 一致性 | 数据的一致性表明了一个可靠的趋势。 | ||
| 统一性 | Uniformity in production processes can lead to higher quality products. | 生产过程中的统一性可以提高产品质量。 |
例句
1.The project manager highlighted the variances between planned and actual timelines in the project review.
项目经理在项目评审中强调了计划时间与实际时间之间的差异。
2.Management is concerned about the variances in sales figures compared to last quarter.
管理层对与上个季度相比的销售数字中的差异感到担忧。
3.The quality control team analyzed the variances in product dimensions to ensure compliance with specifications.
质量控制团队分析了产品尺寸中的差异，以确保符合规格。
4.The accountant reported several variances in the budget, indicating areas where spending exceeded expectations.
会计报告了预算中几个差异，表明支出超出了预期的领域。
5.In statistical analysis, understanding the variances helps in assessing data reliability.
在统计分析中，理解方差有助于评估数据的可靠性。
作文
In the world of statistics and data analysis, understanding the concept of variances is crucial for interpreting data accurately. Variances (方差) measure how much a set of numbers differs from their average value, providing insights into the distribution and spread of data points. When analyzing data, researchers often seek to understand not just the mean but also the variances (方差), as this information can reveal underlying patterns that may not be immediately obvious.For instance, consider a classroom where students' test scores are analyzed. If all students scored around 80, the variances (方差) would be low, indicating that most students performed similarly. However, if some students scored as low as 50 while others scored as high as 100, the variances (方差) would be high, highlighting significant differences in performance. This is essential for educators who want to tailor their teaching strategies to meet diverse learning needs.Moreover, variances (方差) play a pivotal role in fields such as finance and economics. Investors often look at the variances (方差) of asset returns to gauge risk. A higher variances (方差) indicates greater volatility, which can lead to higher potential returns but also increases the risk of loss. Understanding these variances (方差) helps investors make informed decisions about where to allocate their resources.In scientific research, the calculation of variances (方差) is equally important. Researchers utilize variances (方差) to determine whether observed differences in experimental results are statistically significant. For example, if a new drug shows a different effect on two groups of patients, analyzing the variances (方差) in their responses can help scientists conclude whether the drug is effective or if the differences were due to random chance.Furthermore, when conducting surveys or experiments, understanding the variances (方差) allows researchers to assess the reliability of their findings. A small variances (方差) suggests that the data is consistent and reliable, while a large variances (方差) may indicate issues with the data collection process or the need for further investigation.In conclusion, variances (方差) are a fundamental concept in statistics that provide valuable insights across various fields, including education, finance, and scientific research. By measuring how much data points differ from the mean, variances (方差) enable analysts and researchers to understand trends, assess risks, and draw meaningful conclusions. As we continue to navigate a data-driven world, mastering the concept of variances (方差) will undoubtedly enhance our ability to interpret information and make informed decisions.
在统计学和数据分析的世界中，理解variances(方差)的概念对于准确解读数据至关重要。Variances(方差)衡量一组数字与其平均值之间的差异，提供有关数据点的分布和散布的洞察。当分析数据时，研究人员通常寻求理解不仅仅是均值，还有variances(方差)，因为这些信息可以揭示潜在的模式，这些模式可能并不立即明显。例如，考虑一个教室，学生的考试成绩被分析。如果所有学生的得分都在80左右，则variances(方差)将很低，表明大多数学生表现相似。然而，如果一些学生得分低至50，而其他学生得分高达100，则variances(方差)将很高，突显出表现的显著差异。这对于希望量身定制教学策略以满足不同学习需求的教育工作者至关重要。此外，variances(方差)在金融和经济等领域发挥着关键作用。投资者通常查看资产回报的variances(方差)来评估风险。较高的variances(方差)表示更大的波动性，这可能导致更高的潜在回报，但也增加了损失的风险。理解这些variances(方差)有助于投资者做出明智的资源配置决策。在科学研究中，计算variances(方差)同样重要。研究人员利用variances(方差)来确定实验结果中观察到的差异是否具有统计学意义。例如，如果一种新药对两组患者的影响不同，分析他们反应的variances(方差)可以帮助科学家得出药物是否有效的结论，或者差异是否由于随机机会造成。此外，在进行调查或实验时，理解variances(方差)使研究人员能够评估其发现的可靠性。较小的variances(方差)表明数据是一致且可靠的，而较大的variances(方差)可能表明数据收集过程存在问题或需要进一步调查。总之，variances(方差)是统计学中的一个基本概念，在教育、金融和科学研究等多个领域提供了宝贵的洞察。通过测量数据点与均值之间的差异，variances(方差)使分析师和研究人员能够理解趋势、评估风险并得出有意义的结论。随着我们继续在数据驱动的世界中航行，掌握variances(方差)的概念无疑将增强我们解读信息和做出明智决策的能力。
