derived estimate

简明释义

导出估价值

英英释义

例句

1.The derived estimate for the completion time was significantly lower than expected.

完成时间的派生估算明显低于预期。

2.The project manager provided a derived estimate for the budget based on previous projects.

项目经理根据之前的项目提供了一个派生估算的预算。

3.The financial analyst's derived estimate indicated a strong growth trend in the market.

金融分析师的派生估算显示市场有强劲的增长趋势。

4.Using historical data, the team created a derived estimate for the new product launch.

团队使用历史数据为新产品发布创建了一个派生估算。

5.After analyzing the data, we produced a derived estimate of the potential sales for next quarter.

在分析数据后，我们得出了下个季度潜在销售的派生估算。

作文

In the field of statistics and data analysis, the term derived estimate refers to a value that is calculated based on other values or data points. This concept is crucial for researchers and analysts who often work with incomplete data sets or need to make predictions based on existing information. A derived estimate allows them to fill in gaps and provide more comprehensive insights. For instance, if a researcher is studying the average height of a population but only has data from a small sample, they might use the derived estimate to predict the average height of the entire population by applying statistical methods such as regression analysis.Understanding how to create and utilize derived estimates is essential for making informed decisions. In many cases, these estimates can help businesses forecast sales, plan budgets, or assess risks. For example, a company may analyze past sales data to create a derived estimate of future sales trends. This information can be invaluable for strategic planning and resource allocation.Moreover, the accuracy of a derived estimate heavily relies on the quality of the initial data. If the base data is flawed or biased, the resulting estimate will likely be inaccurate as well. Therefore, it is critical for analysts to ensure that their foundational data is reliable before proceeding with calculations. This highlights the importance of data integrity and validation in the process of deriving estimates.In addition to its applications in business and research, the concept of derived estimates is also prevalent in the field of finance. Financial analysts frequently use derived estimates to evaluate the potential returns of investments. By analyzing historical performance data and market trends, they can create projections that guide investment strategies. These estimates are not only useful for individual investors but also for large institutions that manage substantial portfolios.Furthermore, the use of derived estimates extends into various sectors, including healthcare, environmental science, and engineering. In healthcare, for instance, doctors may use derived estimates to predict patient outcomes based on previous cases. Environmental scientists might use models to estimate the impact of climate change on specific ecosystems, relying on derived estimates to inform policy decisions.In conclusion, a derived estimate is a powerful tool that allows individuals and organizations to make educated guesses about unknown values based on known data. Its applications span multiple fields, underscoring its significance in research, business, finance, and beyond. As we continue to navigate an increasingly data-driven world, understanding how to effectively utilize derived estimates will be essential for success. The ability to derive meaningful insights from data not only enhances decision-making processes but also contributes to advancements in various disciplines. Therefore, mastering the concept of derived estimates is a valuable skill for anyone engaged in analytical work.

在统计学和数据分析领域，术语derived estimate指的是基于其他值或数据点计算得出的值。这个概念对于研究人员和分析师至关重要，因为他们常常处理不完整的数据集，或者需要根据现有信息做出预测。derived estimate使他们能够填补空白，提供更全面的见解。例如，如果一名研究人员正在研究一个人群的平均身高，但只有来自小样本的数据，他们可能会使用derived estimate通过应用回归分析等统计方法来预测整个群体的平均身高。理解如何创建和利用derived estimates对做出明智的决策至关重要。在许多情况下，这些估计可以帮助企业预测销售、规划预算或评估风险。例如，一家公司可能会分析过去的销售数据，以创建未来销售趋势的derived estimate。这些信息对于战略规划和资源分配是极其宝贵的。此外，derived estimate的准确性在很大程度上依赖于初始数据的质量。如果基础数据存在缺陷或偏差，那么结果估计也可能不准确。因此，分析师必须确保他们的基础数据可靠，然后再进行计算。这突显了在推导估计过程中数据完整性和验证的重要性。除了在商业和研究中的应用，derived estimates的概念在金融领域也很普遍。金融分析师经常使用derived estimates来评估投资的潜在回报。通过分析历史表现数据和市场趋势，他们可以创建指导投资策略的预测。这些估计不仅对个人投资者有用，也对管理大量投资组合的大型机构至关重要。此外，derived estimates的使用还扩展到多个领域，包括医疗保健、环境科学和工程学。在医疗保健中，例如，医生可能会使用derived estimates预测患者的结果，基于先前的案例。环境科学家可能会利用模型估计气候变化对特定生态系统的影响，依赖于derived estimates来为政策决策提供信息。总之，derived estimate是一种强大的工具，使个人和组织能够根据已知数据对未知值做出明智的猜测。它的应用跨越多个领域，强调了它在研究、商业、金融及其他领域的重要性。随着我们继续在一个日益以数据驱动的世界中航行，理解如何有效利用derived estimates将对成功至关重要。从数据中推导出有意义的见解不仅增强了决策过程，还有助于各个学科的进步。因此，掌握derived estimates的概念对于任何从事分析工作的人来说都是一项宝贵的技能。