cumulative error

简明释义

累积误差

英英释义

例句

1.Engineers must account for cumulative error 累积误差 when designing precise instruments.

工程师在设计精密仪器时必须考虑到累积误差。

2.To minimize cumulative error 累积误差, it's important to check calculations regularly.

为了最小化累积误差，定期检查计算非常重要。

3.In long calculations, a small mistake can lead to a significant cumulative error 累积误差 by the end.

在长时间的计算中，一个小错误可能会导致到最后出现显著的累积误差。

4.In scientific experiments, cumulative error 累积误差 can skew results dramatically.

在科学实验中，累积误差可能会严重扭曲结果。

5.The software update fixed the cumulative error 累积误差 that had been affecting data accuracy.

软件更新修复了影响数据准确性的累积误差。

作文

In the realm of mathematics and science, precision is paramount. However, in practical applications, achieving absolute accuracy can be quite challenging. This is where the concept of cumulative error comes into play. 累积误差 refers to the total amount of error that accumulates in a series of measurements or calculations. It is crucial to understand how this error can affect our results, especially when performing experiments or calculations that require multiple steps.For instance, consider a simple experiment where we are measuring the length of a table. If we use a ruler that is slightly miscalibrated, each measurement we take will be off by a small amount. Initially, this might seem negligible, but as we continue to take multiple measurements, the errors begin to add up. After several measurements, the total error could significantly deviate from the actual length of the table. This scenario illustrates how cumulative error can lead to misleading conclusions.In engineering, cumulative error is a critical factor that must be accounted for during the design and testing phases of a project. For example, if an engineer is designing a bridge and uses flawed measurements for key components, the 累积误差 could compromise the integrity of the structure. Engineers often utilize methods such as error analysis to minimize the impact of these errors, ensuring that their designs are as accurate as possible.Moreover, in the field of data analysis, cumulative error can significantly influence the outcomes of statistical models. When data is collected over time, any inaccuracies in the initial data points can lead to skewed results. For instance, if a researcher is tracking changes in population over several years, even a small error in the initial count can lead to large discrepancies in the final analysis. This emphasizes the importance of meticulous data collection and verification processes to mitigate 累积误差.Furthermore, the concept of cumulative error is not limited to scientific fields; it also extends to everyday life. Consider a situation where someone is following a recipe. If they consistently mismeasure one ingredient, the cumulative effect of that error can result in a dish that tastes completely different from what was intended. This example highlights how 累积误差 can permeate various aspects of our daily routines, affecting outcomes in ways we may not immediately recognize.To mitigate the effects of cumulative error, it is essential to adopt best practices in measurement and calculation. This includes using calibrated tools, double-checking measurements, and being aware of potential sources of error. Additionally, employing statistical techniques to analyze the data can help identify and correct for any 累积误差 present in the results.In conclusion, understanding cumulative error is vital across various disciplines. Whether in scientific research, engineering projects, or even cooking, recognizing how errors accumulate can help us strive for greater accuracy and improve our outcomes. By adopting careful measurement practices and being mindful of potential errors, we can work towards reducing the impact of 累积误差 in our endeavors.