weightings

简明释义

英[ˈweɪtɪŋz]美[ˈweɪtɪŋz]

n. [数]权重（weighting 的复数）；加权数

英英释义

单词用法

同义词

反义词

例句

1.After the extended directed graph with weightings for describing product information is introduced, the changes of product data model during different stages of design and manufacturing are studied.

在介绍描述产品信息的扩展赋权有向图之后，研究了产品数据模型在设计与制造过程不同阶段的变化。

2.These weightings can and should change as the product evolves. Anytime planning is being done the weights should be re-evaluated.

随着产品的演化，这些权重可以而且应该发生变化。

3.The weightings can change over time, as nuances or tendencies emerge.

加权值会因时间而改变，比如出现细微差别或倾向。

4.The U. S. system USES six different capital weightings for bonds according to their credit risk, and the Japanese system USES three.

美国的体制根据债券的信贷风险对债券使用六种不同的资本权重，而日本的体制只使用三种。

5.But regulatory and accounting pressures are instead forcing them to increase their bond weightings; hedge funds end up being substituted for equities instead.

但是监管和会计压力代替了他们提高债券比重的压力；对冲基金结束替代股票。

6.They should give extra weightings to exclusive restaurants, hotels and clubs, as well as access to top of the range luxury products and services and proximity of important cultural events.

他们应该给专享饭店、酒店和俱乐部更高的权重，还有获得高档奢侈品和服务的方便与否，以及享受重要文化活动的便利性。

7.In our investment strategy, we apply specific weightings 权重 to various asset classes based on their risk profiles.

在我们的投资策略中，我们根据不同资产类别的风险特征应用特定的weightings权重。

8.The project manager explained how the weightings 权重 for each criterion affected the overall evaluation.

项目经理解释了每个标准的weightings权重如何影响整体评估。

9.When calculating the index, different sectors have varying weightings 权重 that reflect their market value.

在计算指数时，不同部门有不同的weightings权重，反映其市场价值。

10.The survey results were adjusted for demographic weightings 权重 to ensure accuracy.

调查结果经过人口统计学的weightings权重调整，以确保准确性。

11.The final grade for the course is determined by different weightings 权重 assigned to assignments and exams.

这门课程的最终成绩由不同的weightings权重分配给作业和考试决定。

作文

In today's data-driven world, the concept of weightings (权重) plays a crucial role in various fields, including statistics, finance, and decision-making processes. Weightings refer to the importance or influence assigned to different variables or components within a dataset or model. Understanding how to apply weightings (权重) effectively can significantly enhance the accuracy and relevance of analyses, leading to better-informed decisions.To illustrate the significance of weightings (权重), consider a simple example from education. When calculating a student's final grade, different assignments might be assigned different levels of importance. For instance, a midterm exam could have a weighting of 50%, while homework assignments might carry a weighting of 20%. In this case, the final grade is not merely an average of all scores; instead, it reflects the varying importance of each component, with the midterm exam having a greater impact on the overall result. This use of weightings (权重) ensures that the final evaluation accurately represents the student's performance based on the significance of each task.In finance, weightings (权重) are essential for portfolio management. Investors often allocate different percentages of their capital to various assets, reflecting their confidence in each asset's potential return. For example, an investor might assign a 60% weighting to stocks, 30% to bonds, and 10% to alternative investments. This strategic allocation allows the investor to manage risk while aiming for optimal returns. By adjusting the weightings (权重) of each asset class, the investor can respond to market changes and personal financial goals more effectively.Moreover, in statistical modeling, weightings (权重) help refine predictions by accounting for the varying significance of different predictors. For instance, when developing a regression model to predict housing prices, factors such as location, size, and age of the property may not contribute equally to the prediction. By applying appropriate weightings (权重) to these variables, analysts can improve the model's accuracy, leading to more reliable forecasts. This practice highlights the importance of understanding the context and relevance of each variable when determining its weighting (权重).In conclusion, the concept of weightings (权重) is integral to various disciplines where data analysis and decision-making are involved. Whether in education, finance, or statistical modeling, effective application of weightings (权重) enhances the quality of outcomes and supports better decisions. As we continue to navigate an increasingly complex world, mastering the use of weightings (权重) will remain a valuable skill for individuals and organizations alike. Understanding how to assign appropriate weightings (权重) allows for a more nuanced approach to analysis, ultimately leading to improved performance and success in various endeavors.

在当今数据驱动的世界中，weightings（权重）这一概念在统计学、金融和决策过程中发挥着至关重要的作用。权重是指在数据集或模型中分配给不同变量或组件的重要性或影响力。有效理解如何应用weightings（权重）可以显著提高分析的准确性和相关性，从而做出更明智的决策。为了说明weightings（权重）的重要性，可以考虑一个来自教育的简单例子。当计算学生的最终成绩时，不同的作业可能被赋予不同的重视程度。例如，期中考试可能有50%的权重，而家庭作业可能占20%的权重。在这种情况下，最终成绩不仅仅是所有分数的平均值；相反，它反映了每个组成部分的不同重要性，其中期中考试对整体结果的影响更大。这种对weightings（权重）的使用确保了最终评估准确地代表了学生的表现，基于每项任务的重要性。在金融领域，weightings（权重）对于投资组合管理至关重要。投资者通常会将资本的不同百分比分配给各种资产，以反映他们对每项资产潜在回报的信心。例如，投资者可能会将60%的权重分配给股票，30%分配给债券，10%分配给另类投资。这种战略性分配使投资者能够在追求最佳回报的同时管理风险。通过调整每个资产类别的weightings（权重），投资者可以更有效地应对市场变化和个人财务目标。此外，在统计建模中，weightings（权重）通过考虑不同预测变量的重要性来帮助精细化预测。例如，当开发一个回归模型来预测房价时，位置、大小和房产年龄等因素可能对预测的贡献并不相等。通过对这些变量应用适当的weightings（权重），分析师可以提高模型的准确性，从而得出更可靠的预测。这一做法强调了在确定每个变量的weightings（权重）时理解其背景和相关性的重要性。总之，weightings（权重）这一概念在涉及数据分析和决策制定的各个学科中都是不可或缺的。无论是在教育、金融还是统计建模中，有效应用weightings（权重）都能提高结果的质量，并支持更好的决策。随着我们继续在日益复杂的世界中航行，掌握weightings（权重）的使用将仍然是个人和组织的一项宝贵技能。理解如何分配适当的weightings（权重）使分析能够采取更细致的方法，最终在各项事业中实现更好的表现和成功。