determinate error

简明释义

预计误差

英英释义

例句

1.In statistical analysis, determinate error can lead to systematic bias in the data interpretation.

在统计分析中，确定性误差可能导致数据解释中的系统偏差。

2.Understanding determinate error helps improve the accuracy of scientific measurements.

理解确定性误差有助于提高科学测量的准确性。

3.The scientist noted a determinate error in the measurement due to calibration issues.

科学家注意到测量中由于校准问题产生了确定性误差。

4.When conducting experiments, it is crucial to identify any determinate error that may skew the results.

在进行实验时，识别任何可能影响结果的确定性误差至关重要。

5.The technician adjusted the device to minimize determinate error during the testing phase.

技术人员调整设备以最小化测试阶段的确定性误差。

作文

In the field of science and engineering, precision is paramount. When conducting experiments or measurements, researchers strive to obtain accurate results. However, achieving perfect accuracy is often an elusive goal due to various factors that can introduce errors into the process. One such type of error is known as determinate error, which refers to errors that have a specific cause and can be identified and corrected. Understanding determinate error is essential for anyone involved in quantitative research, as it directly impacts the reliability of the data collected.To illustrate the concept of determinate error, consider a scenario in which a scientist measures the temperature of a substance using a thermometer. If the thermometer is improperly calibrated, it may consistently read higher or lower than the true temperature. This consistent deviation is a classic example of determinate error. Unlike random errors, which fluctuate unpredictably, determinate error can be traced back to a specific source, such as faulty equipment or improper measurement techniques.There are several common sources of determinate error. One of the most prevalent is instrument bias, where the measuring device has an inherent flaw that skews the results. For instance, if a scale is not zeroed correctly, every weight measured will be off by a fixed amount. Another source is environmental conditions; for example, temperature fluctuations can affect the readings of sensitive instruments. Additionally, human error can also contribute to determinate error. If a researcher misreads a measurement or records data incorrectly, this will lead to systematic inaccuracies.The implications of determinate error in research cannot be overstated. When researchers fail to account for these errors, they risk drawing incorrect conclusions from their data. For instance, in a clinical trial, if the dosage of a medication is measured incorrectly due to a determinate error in the measuring device, the results could suggest that the drug is either more or less effective than it truly is. This could have serious consequences for patient safety and treatment efficacy.To mitigate the effects of determinate error, researchers must implement rigorous testing and calibration procedures. Regularly calibrating instruments, conducting multiple trials, and using control groups can help identify and correct these errors before they compromise the integrity of the study. Furthermore, documenting all methods and potential sources of error allows for transparency and reproducibility in research.In conclusion, understanding determinate error is crucial for anyone involved in scientific research. By recognizing the specific causes of these errors and taking steps to minimize their impact, researchers can enhance the accuracy and reliability of their findings. Ultimately, this leads to more trustworthy data, which is essential for advancing knowledge and ensuring the validity of scientific inquiry. In a world where data-driven decisions are increasingly important, being aware of and addressing determinate error is a responsibility that every researcher must embrace.

在科学和工程领域，精确性至关重要。在进行实验或测量时，研究人员努力获取准确的结果。然而，由于多种因素可能会引入错误，达到完美的准确性往往是一个难以捉摸的目标。其中一种错误称为确定性误差，它指的是具有特定原因、可以被识别和纠正的错误。理解确定性误差对任何参与定量研究的人来说都是至关重要的，因为它直接影响所收集数据的可靠性。为了说明确定性误差的概念，考虑一个场景，科学家使用温度计测量物质的温度。如果温度计校准不当，它可能始终比真实温度高或低。这种一致的偏差就是确定性误差的经典例子。与随机误差不同，随机误差是不规律波动的，而确定性误差可以追溯到特定来源，例如故障设备或不当的测量技术。确定性误差的几个常见来源之一是仪器偏差，即测量设备存在固有缺陷，导致结果偏差。例如，如果秤没有正确归零，则每个测量的重量都会偏离固定的数值。另一个来源是环境条件；例如，温度波动可能会影响敏感仪器的读数。此外，人为错误也可能导致确定性误差。如果研究人员错误读取测量结果或记录数据不正确，这将导致系统性的不准确。在研究中，确定性误差的影响不可小觑。当研究人员未能考虑这些错误时，他们就冒着从数据中得出不正确结论的风险。例如，在临床试验中，如果由于测量设备的确定性误差而错误测量药物剂量，结果可能会表明该药物的效果比实际情况要好或差。这可能对患者安全和治疗效果产生严重后果。为了减轻确定性误差的影响，研究人员必须实施严格的测试和校准程序。定期校准仪器、进行多次试验以及使用对照组可以帮助在研究完整性受到损害之前识别和纠正这些错误。此外，记录所有方法和潜在错误来源可以确保研究的透明性和可重复性。总之，理解确定性误差对任何参与科学研究的人至关重要。通过识别这些错误的具体原因并采取措施最小化其影响，研究人员可以提高其发现的准确性和可靠性。最终，这将导致更值得信赖的数据，这对促进知识进步和确保科学探究的有效性至关重要。在一个数据驱动决策日益重要的世界里，意识到并解决确定性误差是每位研究人员必须承担的责任。