{"title":"教学实验室的测不准原理","authors":"K. Haglin","doi":"10.1142/s2661339523500087","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":112108,"journal":{"name":"The Physics Educator","volume":"104 9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Uncertainty Principles for Teaching Laboratories\",\"authors\":\"K. Haglin\",\"doi\":\"10.1142/s2661339523500087\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":112108,\"journal\":{\"name\":\"The Physics Educator\",\"volume\":\"104 9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Physics Educator\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1142/s2661339523500087\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Physics Educator","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/s2661339523500087","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.