sensitivity analysis

简明释义

敏感响应分析

英英释义

例句

1.Before launching the new product, the marketing department performed a sensitivity analysis to gauge customer responses under different pricing strategies.

在推出新产品之前，市场部门进行了敏感性分析，以评估客户在不同定价策略下的反应。

2.The project manager used sensitivity analysis to identify which variables had the most significant effect on the project's overall success.

项目经理使用敏感性分析来识别哪些变量对项目整体成功有最显著的影响。

3.The sensitivity analysis revealed that small changes in the input data could lead to large differences in the output.

这项敏感性分析显示，输入数据的微小变化可能导致输出结果的巨大差异。

4.The finance team conducted a sensitivity analysis to understand how changes in interest rates would impact the company's profits.

财务团队进行了敏感性分析，以了解利率变化将如何影响公司的利润。

5.In their research, the scientists included a sensitivity analysis to determine how variations in temperature could affect the results of their experiments.

在他们的研究中，科学家们进行了敏感性分析，以确定温度变化如何影响实验结果。

作文

In the field of decision-making and risk management, sensitivity analysis plays a crucial role. It is a method used to predict the outcome of a decision given a certain range of variables. By examining how different values of an independent variable affect a particular dependent variable under a given set of assumptions, analysts can determine which variables have the most impact on the outcome. This process is especially important in financial modeling, where small changes in assumptions can lead to significantly different results.For instance, consider a company that is evaluating a new project. The projected cash flows from this project may depend on various factors such as market demand, production costs, and competition. By conducting a sensitivity analysis, the company can identify which of these factors are most critical to the project's success. If the analysis reveals that the project's viability is highly sensitive to changes in market demand, the company can focus its efforts on researching market trends and consumer preferences.Moreover, sensitivity analysis can help organizations understand the risks associated with their decisions. In uncertain environments, it is essential to know how much variation in output can be expected from variations in input. For example, if a financial analyst is forecasting profits based on several assumptions about sales growth, interest rates, and operating expenses, a sensitivity analysis can show how changes in these assumptions could affect the final profit figure. This insight allows managers to make more informed decisions by understanding the potential range of outcomes.Another application of sensitivity analysis is in environmental studies. Researchers often use this method to assess how changes in environmental factors can impact ecological systems. For instance, if scientists want to understand how temperature changes might affect a specific species' habitat, they can conduct a sensitivity analysis to see how varying temperature scenarios would influence the species' survival and reproduction rates. This information is vital for policymakers who need to develop strategies for conservation and resource management.Furthermore, sensitivity analysis is not limited to financial or environmental applications. It can also be applied in engineering, healthcare, and various other fields. For example, in engineering, designers can use sensitivity analysis to evaluate how changes in material properties affect the performance of a structure. In healthcare, it can be used to study how different treatment plans might affect patient outcomes, helping doctors choose the best course of action.In conclusion, sensitivity analysis is a powerful tool that aids in understanding the relationship between variables and the potential impact of uncertainty in decision-making processes. By identifying which variables are most influential, organizations can allocate resources more effectively, mitigate risks, and make better-informed decisions. As the complexity of systems and the uncertainty of the environment increase, the importance of sensitivity analysis will only continue to grow, highlighting its value across multiple disciplines and industries.

在决策和风险管理领域，sensitivity analysis（敏感性分析）发挥着至关重要的作用。这是一种用于预测在一定范围内变量给定的决策结果的方法。通过检查独立变量的不同值如何影响特定的依赖变量，在给定的一系列假设下，分析师可以确定哪些变量对结果影响最大。这个过程在财务建模中尤其重要，因为假设的微小变化可能导致显著不同的结果。例如，考虑一家正在评估新项目的公司。该项目的预计现金流可能依赖于各种因素，如市场需求、生产成本和竞争。通过进行sensitivity analysis（敏感性分析），公司可以识别出哪些因素对项目的成功至关重要。如果分析表明，该项目的可行性对市场需求的变化高度敏感，公司可以集中精力研究市场趋势和消费者偏好。此外，sensitivity analysis（敏感性分析）可以帮助组织理解其决策所涉及的风险。在不确定的环境中，了解输入的变化可能会导致输出的变化量是至关重要的。例如，如果一位财务分析师正在根据关于销售增长、利率和运营费用的多个假设来预测利润，sensitivity analysis（敏感性分析）可以显示这些假设的变化将如何影响最终的利润数字。这一见解使管理者能够通过了解潜在的结果范围来做出更明智的决策。sensitivity analysis（敏感性分析）的另一个应用是在环境研究中。研究人员经常使用这种方法来评估环境因素的变化如何影响生态系统。例如，如果科学家想了解温度变化可能如何影响特定物种的栖息地，他们可以进行sensitivity analysis（敏感性分析），以查看不同温度情景将如何影响该物种的生存和繁殖率。这些信息对于需要制定保护和资源管理策略的政策制定者至关重要。此外，sensitivity analysis（敏感性分析）并不限于财务或环境应用。它还可以应用于工程、医疗保健和其他各个领域。例如，在工程中，设计师可以使用sensitivity analysis（敏感性分析）来评估材料属性的变化如何影响结构的性能。在医疗保健中，它可以用来研究不同治疗方案可能对患者结果产生的影响，帮助医生选择最佳的行动方案。总之，sensitivity analysis（敏感性分析）是一种强大的工具，有助于理解变量之间的关系以及不确定性在决策过程中的潜在影响。通过识别最具影响力的变量，组织可以更有效地分配资源，减轻风险，并做出更明智的决策。随着系统复杂性的增加和环境不确定性的加剧，sensitivity analysis（敏感性分析）的重要性只会继续增长，突显其在多个学科和行业中的价值。