effective error; real error; actual error

简明释义

实际误差

英英释义

Effective error refers to the error that has a significant impact on the outcome of a process or measurement, often taking into account various factors that contribute to its overall effect.

有效误差是指对过程或测量结果产生重大影响的误差,通常考虑到各种因素对其整体效果的贡献。

Real error denotes the actual discrepancy between the measured value and the true value, highlighting the inherent inaccuracies in measurements.

真实误差表示测量值与真实值之间的实际差异,突显了测量中的固有不准确性。

Actual error is the difference between the observed value and the exact value, which can be quantified and analyzed to improve accuracy.

实际误差是观测值与精确值之间的差异,可以量化和分析以提高准确性。

例句

1.The software update reduced the effective error 有效误差 in data processing significantly.

软件更新显著减少了数据处理中的有效误差 有效误差

2.We need to calculate the effective error 有效误差 to ensure the reliability of the experiment.

我们需要计算有效误差 有效误差以确保实验的可靠性。

3.The technician explained that the real error 真实误差 could be minimized with better equipment.

技术员解释说,通过更好的设备可以最小化真实误差 真实误差

4.The actual error 实际误差 in the final report was less than anticipated due to improved accuracy.

由于精度提高,最终报告中的实际误差 实际误差低于预期。

5.After recalibrating the instruments, we noticed a decrease in the real error 真实误差 of our measurements.

在重新校准仪器后,我们注意到测量中的真实误差 真实误差有所减少。

作文

In the realm of mathematics and science, the concept of error plays a crucial role in determining the accuracy and reliability of measurements and calculations. Understanding the distinctions between effective error(有效误差), real error(真实误差), and actual error(实际误差) is essential for anyone engaged in research or practical applications. Each type of error provides insight into the precision of our results and helps us refine our methodologies. Firstly, let’s define these terms. The effective error refers to the error that has a significant impact on the outcomes of a measurement or calculation. It encompasses all factors that can distort the true value, including systematic errors and random errors. This type of error is particularly important when making decisions based on data, as it directly influences the effectiveness of the conclusions drawn from the results. For instance, if a scientist is measuring the boiling point of water, the effective error might include inaccuracies due to faulty equipment or environmental conditions, which could lead to an incorrect understanding of the boiling point under different circumstances.On the other hand, the real error is often considered the theoretical difference between the measured value and the true value. It represents the error that would exist if all possible factors were accounted for and eliminated. In practice, achieving zero real error is nearly impossible due to the myriad variables that can affect measurements. However, understanding real error helps researchers identify potential sources of discrepancies in their work. For example, if a researcher is aware that their measuring instrument has a known bias, they can adjust their calculations to minimize the real error in their findings.Lastly, the actual error is the difference between the measured value and the accepted true value at the moment of measurement. This type of error can be quantified and is often expressed in absolute terms. For example, if the accepted boiling point of water is 100 degrees Celsius, and a measurement yields 99.5 degrees Celsius, the actual error is 0.5 degrees Celsius. The actual error is crucial for assessing the performance of measurement instruments and for calibrating them to ensure accuracy.In conclusion, the distinctions between effective error, real error, and actual error are vital for anyone involved in scientific inquiry or any field that relies on precise measurements. By comprehensively understanding these types of errors, researchers can improve the reliability of their work, make more informed decisions, and contribute to the advancement of knowledge. Moreover, this understanding fosters a culture of continuous improvement, where errors are not merely seen as failures but as opportunities for growth and refinement in pursuit of accuracy. Thus, mastering these concepts is not just an academic exercise; it is a fundamental skill that enhances the quality of scientific endeavors.

在数学和科学领域,误差的概念在确定测量和计算的准确性和可靠性方面起着至关重要的作用。理解有效误差(有效误差)、真实误差(真实误差)和实际误差(实际误差)之间的区别,对于任何从事研究或实际应用的人来说都是必不可少的。每种类型的误差都提供了对结果精确度的洞察,并帮助我们完善我们的研究方法。首先,让我们定义这些术语。有效误差是指对测量或计算结果产生显著影响的误差。它包含所有可能扭曲真实值的因素,包括系统误差和随机误差。这种类型的误差在基于数据做出决策时尤其重要,因为它直接影响得出的结论的有效性。例如,如果一位科学家正在测量水的沸点,有效误差可能包括由于设备故障或环境条件造成的不准确,这可能导致对不同情况下沸点的理解不正确。另一方面,真实误差通常被认为是测量值与真实值之间的理论差异。它代表如果所有可能的因素都被考虑并消除,所存在的误差。在实践中,实现零真实误差几乎是不可能的,因为有无数变量可能会影响测量。然而,理解真实误差可以帮助研究人员识别其工作中的潜在差异来源。例如,如果研究人员知道他们的测量仪器有已知偏差,他们可以调整计算以最小化其发现中的真实误差。最后,实际误差是指在测量时测量值与公认真实值之间的差异。这种类型的误差可以量化,通常以绝对值表示。例如,如果水的公认沸点为100摄氏度,而测量得到99.5摄氏度,则实际误差为0.5摄氏度。实际误差对于评估测量仪器的性能和校准它们以确保准确性至关重要。总之,有效误差真实误差实际误差之间的区别对于任何参与科学研究或依赖精确测量的领域的人都是至关重要的。通过全面理解这些类型的误差,研究人员可以提高其工作的可靠性,做出更明智的决策,并为知识的进步做出贡献。此外,这种理解促进了一种持续改进的文化,在这种文化中,错误不仅仅被视为失败,而是作为在追求准确性过程中成长和完善的机会。因此,掌握这些概念不仅仅是学术练习;它是一项基本技能,可以提高科学事业的质量。