range adjustment

简明释义

距离调整

英英释义

例句

1.The software update included a range adjustment feature to enhance user experience.

软件更新包含了一个范围调整功能，以增强用户体验。

2.The technician performed a range adjustment to ensure the device operates within its optimal parameters.

技术人员进行了范围调整以确保设备在最佳参数内运行。

3.The coach suggested a range adjustment in training intensity to prevent injuries.

教练建议在训练强度上进行范围调整以防止受伤。

4.After testing, we found that the range adjustment improved the accuracy of the measurements.

测试后，我们发现范围调整提高了测量的准确性。

5.In the calibration process, the engineer made a necessary range adjustment to the sensors.

在校准过程中，工程师对传感器进行了必要的范围调整。

作文

In the realm of data analysis and statistics, the term range adjustment refers to the process of modifying the range of a dataset to improve its interpretability or to meet specific analytical requirements. This technique is particularly useful when dealing with datasets that exhibit significant variability or when preparing data for visual representation. For instance, when plotting a graph, if the data points are too spread out, it can be challenging to discern patterns or trends. By applying range adjustment, analysts can rescale the data, thereby making the visualization more effective and insightful.One common method of range adjustment involves normalization, where data values are transformed to fit within a specified range, typically between 0 and 1. This is particularly important in machine learning applications, where features with larger ranges can disproportionately influence the performance of algorithms. By normalizing the data, we ensure that each feature contributes equally to the model's predictions, leading to improved accuracy and reliability.Another approach to range adjustment is standardization, which involves centering the data around the mean and scaling it based on the standard deviation. This method is beneficial when the data follows a Gaussian distribution, as it allows for better comparison across different datasets. In practice, range adjustment can help mitigate issues related to outliers, ensuring that they do not skew the results of statistical analyses.Furthermore, range adjustment plays a crucial role in financial modeling and forecasting. In these contexts, analysts often need to compare historical data against current market conditions. By adjusting the ranges of various financial metrics, such as stock prices or revenue figures, analysts can create a more accurate picture of performance over time. This adjustment enables stakeholders to make informed decisions based on consistent and comparable data.Moreover, range adjustment is not limited to quantitative data. In qualitative research, researchers may also apply adjustments to categorical data to ensure that the categories are evenly distributed. For example, if one category has significantly more responses than others, researchers might combine similar categories to achieve a more balanced representation. This process of adjustment can enhance the validity of the research findings and provide a clearer understanding of the underlying trends.In conclusion, the concept of range adjustment is integral to effective data analysis and interpretation. Whether through normalization, standardization, or other methods, adjusting the range of data enables analysts to derive meaningful insights and make informed decisions. As we continue to navigate an increasingly data-driven world, mastering techniques like range adjustment will be essential for anyone looking to excel in fields that rely on data analysis, from finance to social sciences. Understanding how to properly adjust ranges not only enhances the quality of our analyses but also empowers us to communicate our findings more effectively to diverse audiences.

范围调整这个术语在数据分析和统计领域中，指的是修改数据集范围的过程，以提高其可解释性或满足特定的分析要求。这项技术在处理具有显著变异性的数据集时尤为有用，或者在准备数据进行可视化展示时。例如，在绘制图表时，如果数据点过于分散，可能很难辨别出模式或趋势。通过应用范围调整，分析师可以重新缩放数据，从而使可视化效果更有效、更具洞察力。范围调整的一种常见方法是归一化，其中数据值被转换为适应指定的范围，通常是在0到1之间。这在机器学习应用中尤其重要，因为范围较大的特征可能会不成比例地影响算法的性能。通过对数据进行归一化，我们确保每个特征对模型预测的贡献相等，从而提高准确性和可靠性。另一种范围调整的方法是标准化，它涉及将数据围绕均值进行中心化，并根据标准差进行缩放。当数据遵循高斯分布时，这种方法特别有利，因为它允许不同数据集之间的更好比较。在实践中，范围调整可以帮助减轻与异常值相关的问题，确保它们不会扭曲统计分析的结果。此外，范围调整在金融建模和预测中也起着至关重要的作用。在这些背景下，分析师通常需要将历史数据与当前市场条件进行比较。通过调整各种金融指标的范围，例如股价或收入数字，分析师可以创建更准确的业绩表现图景。这种调整使利益相关者能够基于一致和可比较的数据做出明智的决策。此外，范围调整并不仅限于定量数据。在定性研究中，研究人员也可以对分类数据进行调整，以确保类别均匀分布。例如，如果一个类别的响应数量明显多于其他类别，研究人员可能会合并类似类别以实现更平衡的表示。这种调整过程可以增强研究发现的有效性，并提供对潜在趋势的更清晰理解。总之，范围调整的概念对于有效的数据分析和解释至关重要。无论是通过归一化、标准化还是其他方法，调整数据范围使分析师能够得出有意义的见解并做出明智的决策。随着我们继续在一个日益数据驱动的世界中航行，掌握像范围调整这样的技术将对任何希望在依赖数据分析的领域中脱颖而出的人来说至关重要。了解如何正确调整范围不仅提高了我们分析的质量，还使我们能够更有效地向不同受众传达我们的发现。