total error

简明释义

总误差

英英释义

例句

1.The algorithm's performance was evaluated based on the total error, which is the sum of all discrepancies.

该算法的性能是基于总误差进行评估的，指的是所有差异的总和。

2.Reducing the total error is crucial for improving the reliability of the system.

减少总误差对于提高系统的可靠性至关重要。

3.In the final report, we calculated the total error to understand the accuracy of our predictions.

在最终报告中，我们计算了总误差以了解我们预测的准确性。

4.He explained that the total error could be minimized by using more precise instruments.

他解释说，通过使用更精确的仪器可以最小化总误差。

5.The total error in the measurements was due to several factors including instrument calibration.

测量中的总误差是由于多个因素造成的，包括仪器校准。

作文

In the field of statistics and data analysis, understanding the concept of total error is crucial for accurate interpretation of results. total error refers to the cumulative effect of all errors that can occur during the measurement process. This includes both systematic errors, which are consistent and repeatable inaccuracies due to flaws in the measurement system, and random errors, which arise from unpredictable variations in the measurement environment. A common example of total error can be seen in scientific experiments. Suppose a researcher is measuring the temperature of a substance. If the thermometer used has a calibration error, this would contribute to the systematic part of the total error. On the other hand, fluctuations in room temperature or air pressure at the time of measurement could introduce random errors. The combination of these factors would lead to a total error that affects the reliability of the experiment’s outcome.To minimize total error, researchers often implement rigorous protocols. They may calibrate their instruments before use, conduct multiple trials, and apply statistical methods to analyze the data. For instance, using the average of several measurements can help to reduce the impact of random errors, while identifying and correcting systematic errors can significantly improve the accuracy of the results. In practical applications, such as manufacturing, understanding total error is equally important. Quality control processes often involve measuring various parameters of products to ensure they meet specific standards. If the total error in these measurements is too high, it might indicate that the production process needs adjustment. By analyzing the sources of error, manufacturers can enhance product quality and reduce waste, ultimately leading to increased customer satisfaction.Moreover, in fields like finance or economics, the concept of total error plays a vital role in forecasting and decision-making. Analysts must account for potential errors in their models to provide accurate predictions. If the total error is not adequately addressed, it can lead to significant financial losses or misguided strategic choices. Therefore, incorporating error analysis into financial models is essential for making informed decisions.In conclusion, the understanding of total error is fundamental across various disciplines. Whether in scientific research, manufacturing, or finance, recognizing and addressing the components of total error can lead to more reliable outcomes and better decision-making. As we continue to rely on data-driven approaches in our work, the importance of minimizing total error cannot be overstated. By striving for accuracy and precision, we can enhance the quality of our results and contribute positively to our respective fields.

在统计学和数据分析领域，理解总误差的概念对于准确解读结果至关重要。总误差指的是在测量过程中可能发生的所有误差的累积效应。这包括系统误差，即由于测量系统中的缺陷而导致的一致和可重复的不准确性，以及随机误差，这些误差是由于测量环境中不可预测的变化而产生的。总误差的一个常见例子可以在科学实验中看到。假设一位研究人员正在测量一种物质的温度。如果使用的温度计存在校准误差，这将构成总误差的系统部分。另一方面，测量时房间温度或气压的波动可能会引入随机误差。这些因素的组合将导致影响实验结果可靠性的总误差。为了最小化总误差，研究人员通常会实施严格的协议。他们可能在使用前校准仪器，进行多次试验，并应用统计方法来分析数据。例如，使用多个测量值的平均值可以帮助减少随机误差的影响，而识别和纠正系统误差可以显著提高结果的准确性。在制造等实际应用中，理解总误差同样重要。质量控制过程通常涉及测量产品的各种参数，以确保它们符合特定标准。如果这些测量中的总误差过高，可能表明生产过程需要调整。通过分析误差来源，制造商可以提高产品质量并减少浪费，从而最终提高客户满意度。此外，在金融或经济等领域，总误差的概念在预测和决策中发挥着至关重要的作用。分析师必须考虑模型中的潜在误差，以提供准确的预测。如果没有充分解决总误差，可能会导致重大财务损失或误导性的战略选择。因此，将误差分析纳入金融模型对于做出明智的决策至关重要。总之，理解总误差在各个学科中都是基础。无论是在科学研究、制造还是金融领域，认识到并解决总误差的组成部分可以导致更可靠的结果和更好的决策。随着我们继续依赖数据驱动的方法进行工作，最小化总误差的重要性不容忽视。通过追求准确性和精确性，我们可以提高结果的质量，并对各自的领域作出积极贡献。