Elements of ANOVA in Physics Practice
DOI:
https://doi.org/10.25726/c1624-5010-9548-cKeywords:
dispersion analysis, physical experimentAbstract
Experimental activities are key in the formation of the competencies of students in physical and chemical fields, which is reflected in modern federal educational standards. At the same time, the skills of constructing mathematical models of the studied phenomena acquire particular relevance. Traditionally, when processing the data of a physical experiment, statistical methods are used that make it possible to determine measurement errors, identify outliers, and estimate average values, taking into account absolute and relative errors. Recently, in all areas of natural science knowledge, dispersion analysis has found its application. It is an effective method in the study of experimental data, as it allows you to observe the influence of various factors on the outcome of the experiment. The paper presents an example of expanding these procedures and using analysis of variance in a physics workshop for students of physics at the university. The purpose of this article is to study the possibilities of using analysis of variance when testing the operation of several laboratory instruments for determining the resistivity of a metal. The formulation and solution of such a problem, in the presence of a number of identical settings, gives students the opportunity to expand their understanding of the application of the apparatus of probability theory and mathematical statistics.
References
Гольдварг Т.Б., Петрович Э.В., Сумьянова Е.В. Методика преподавания лабораторного практикума общей физики в высшей школе Современное педагогическое образование. 2020. № 10. С. 41-46.
Корнев К.П., Корнева И.П. Математическая обработка результатов измерений в физическом практикуме // Вестник Балтийского федерального университета им. Канта И. Серия: Физикоматематические и технические науки. 2015. №10.
Маркин Н.С. Основы теории обработки результатов измерений. М.: Изд. стандартов, 1991.
Подживотов Н.Ю. Оценка результатов испытаний с помощью однофакторного дисперсионного анализа // Труды ВИАМ. 2022. № 8 (114). С. 12.
Шеффе Г. Диспеpсионный анализ. М.: Наука, 1980. 512 с.
Budde J., Variance analysis and linear contracts in agencies with distorted performance measures. Management Accounting Research, vol. 20, no. 3, pp. 166-176, 2009.
Тhoma S.J. Pfaff, Sipos Maksim, Sullivan M.C., Thompson B.G., Tran Max M. The Use of Statistics in Experimental Physics Mathematics Magazine 2013 86(2): 120-131.