adjustment computation

简明释义

平差计算;

英英释义

例句

1.The software includes a feature for adjustment computation that automatically updates the figures based on new inputs.

该软件包含一个调整计算功能，可以根据新输入自动更新数字。

2.The financial department performed an adjustment computation to correct the discrepancies in the budget report.

财务部门进行了调整计算以纠正预算报告中的差异。

3.During the audit, the team discovered that an adjustment computation was necessary to reflect accurate sales figures.

在审计过程中，团队发现需要进行调整计算以反映准确的销售数据。

4.The project manager requested an adjustment computation to ensure all expenses were accurately reported.

项目经理请求进行调整计算以确保所有费用都被准确报告。

5.After reviewing the data, the analyst conducted an adjustment computation to account for seasonal variations.

在审查数据后，分析师进行了调整计算以考虑季节性变化。

作文

In the field of mathematics and data analysis, the term adjustment computation refers to the process of recalculating values in order to correct or refine data sets. This concept is crucial when dealing with statistical analyses where initial data may contain errors or biases that can skew results. For instance, in a survey, if a certain demographic is underrepresented, an adjustment computation might be necessary to ensure that the final results accurately reflect the entire population. The importance of adjustment computation cannot be overstated. In research and policy-making, decisions based on flawed data can lead to significant consequences. Therefore, adjusting computations allows researchers to derive more reliable conclusions. One common method of adjustment computation involves weighting responses from different demographics to ensure that each group's influence on the overall outcome is proportional to its actual size in the population. For example, consider a study on consumer preferences where younger individuals are significantly overrepresented. Without adjustment computation, the findings might suggest that younger people prefer a certain product, while in reality, the preferences of older consumers are not accurately reflected. By applying adjustment computation, researchers can apply weights to balance the representation of age groups, leading to a more accurate understanding of consumer behavior. Furthermore, adjustment computation plays a vital role in financial contexts as well. Companies often need to adjust their financial statements to account for various factors such as inflation, currency fluctuations, and economic conditions. These adjustments ensure that stakeholders have a clear and accurate view of the company's performance over time. For instance, if a company’s revenue appears to decline due to inflation, an adjustment computation can help to present a clearer picture of real growth by factoring out the impact of inflation. In addition to its application in surveys and financial reports, adjustment computation is also essential in the realm of machine learning and artificial intelligence. Algorithms often require adjustments to optimize their performance based on the data they process. This could involve tuning parameters or recalibrating models to improve accuracy and reduce bias. The iterative nature of adjustment computation in these fields allows for continuous improvement, ultimately leading to better predictive outcomes. Moreover, the rise of big data has amplified the necessity for effective adjustment computation. With vast amounts of data being generated every second, ensuring the integrity and accuracy of this information is paramount. Data scientists utilize various adjustment computation techniques to clean, validate, and enhance data quality before analysis. This preprocessing step is critical in deriving meaningful insights and making informed decisions based on data analytics. In conclusion, adjustment computation is a fundamental concept that spans across multiple disciplines, including statistics, finance, and technology. Its ability to refine data and provide more accurate representations is invaluable in ensuring that decisions are made based on sound evidence. As we continue to rely on data-driven approaches in various sectors, mastering the principles of adjustment computation will become increasingly important for professionals in these fields.

在数学和数据分析领域，术语调整计算指的是重新计算数值的过程，以便修正或细化数据集。当处理统计分析时，这个概念至关重要，因为初始数据可能包含错误或偏差，从而扭曲结果。例如，在一项调查中，如果某个特定人口群体的代表性不足，则可能需要进行调整计算以确保最终结果准确反映整个群体。

调整计算的重要性不容低估。在研究和政策制定中，基于有缺陷的数据做出的决策可能会导致重大后果。因此，调整计算使研究人员能够得出更可靠的结论。一种常见的调整计算方法涉及对不同人口群体的响应进行加权，以确保每个群体对总体结果的影响与其在总体中的实际规模成比例。

例如，考虑一项关于消费者偏好的研究，其中年轻人显著过度代表。如果没有调整计算，结果可能表明年轻人更喜欢某种产品，而实际上老年消费者的偏好没有得到准确反映。通过应用调整计算，研究人员可以对年龄组进行加权，以平衡代表性，从而更准确地理解消费者行为。

此外，调整计算在财务背景中也发挥着至关重要的作用。公司通常需要调整其财务报表，以考虑通货膨胀、货币波动和经济条件等各种因素。这些调整确保利益相关者对公司业绩有清晰准确的了解。例如，如果由于通货膨胀而导致公司的收入似乎下降，则调整计算可以通过剔除通货膨胀的影响来帮助呈现真实增长的更清晰图景。

除了在调查和财务报告中的应用外，调整计算在机器学习和人工智能领域也至关重要。算法通常需要进行调整，以优化它们基于所处理数据的性能。这可能涉及调整参数或重新校准模型，以提高准确性并减少偏差。在这些领域中，调整计算的迭代性质允许持续改进，最终导致更好的预测结果。

此外，大数据的兴起进一步增强了有效调整计算的必要性。随着每秒生成大量数据，确保这些信息的完整性和准确性至关重要。数据科学家利用各种调整计算技术在分析之前清理、验证和增强数据质量。这一步骤对于得出有意义的见解和基于数据分析做出明智的决策至关重要。

总之，调整计算是一个跨越多个学科的基本概念，包括统计学、金融和技术。它精炼数据并提供更准确表示的能力在确保基于可靠证据做出决策方面是无价的。随着我们在各个领域继续依赖数据驱动的方法，掌握调整计算的原则将变得越来越重要。