教学实验室的测不准原理

K. Haglin
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引用次数: 0

摘要

当涉及到实验室活动时,教育者必须对学习者的期望和技能做出决定。有各种各样的方法,但一般的模式是鼓励学生测量有序对,绘制图表以建立线性相关性,然后计算最佳拟合线的斜率,从而得出最终的科学结论。为了帮助教育工作者,当他们也想包括斜率不确定度依赖于测量不确定度作为预期分析的一部分时,我们展示了一种物理方法,以便教育工作者和他们的学生都有一个方便的路线图可以遵循。教育工作者经常选择的一个流行的替代方案是仅仅依靠统计度量来建立技术的容忍度,但我们认为,统计策略会使学生偏离不确定性的真正含义,而不确定性是在进行测量的行为中固有的。我们将把这些测量误差条从它们的原点通过回归分析来一致地建立斜率和截距的物理误差条。然后,我们用一个介绍性的物理实验来演示这项技术,目的是测量空气中的声速。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Uncertainty Principles for Teaching Laboratories
Educators must make decisions about learner expectations and skills on which to focus when it comes to laboratory activities. There are various approaches but the general pattern is to encourage students to measure ordered pairs, plot a graph to establish linear dependence, and then compute the slope of the best-fit line for an eventual scientific conclusion. To assist educators when they also want to include slope uncertainty dependent upon measurement uncertainty as part of the expected analysis, we demonstrate a physical approach so that both educators and their students have a convenient road map to follow. A popular alternative that educators often choose is to rely solely on statistical metrics to establish the tolerance of the technique, but we argue that the statistical strategy can distract students away from the true meaning of the uncertainty that is inherent in the act of making the measurements. We will carry these measurement error bars from their points of origin through the regression analysis to consistently establish the physical error bars for the slope and the intercept. We then demonstrate the technique using an introductory physics experiment with a purpose of measuring the speed of sound in air.
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CiteScore
0.60
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