COMPARATIVE STATISTICAL ANALYSIS OF PARAMETRICAL AND NONPARAMETRIC METHODS OF THE ESTIMATION OF KNOWLEDGE IN CORRESPONDENCE COURSE SYSTEM

Mihalchuk А.А, Arefyev V.P, Filipenko N.M

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The comparative statistical analysis of parametrical and nonparametric methods of an estimation of quality of correspondence technical education on the basis of three variables is spent: the collected points for 4 individual homeworks (ihw), the collected points for test examination in a condition on-line (ex) and differences of the moments of the termination and the examination beginning (dt). On the basis of criterion a chi-square significant difference of distributions of variables from the normal law is revealed: from statistically significant for ex and to highly significant for dt. Correlation between dt and ex, and also between ihw and ex is estimated as not significant, that is the examination outcome does not depend significantly on time expended on performance of an examination-paper, from quality of tolerance to examination on ihw. Correlation between ihw and dt (r »R» 0,274) strongly significantly differs from 0, nevertheless is rather far from 1. Thus factors of conjugate correlations of Pirson r differ from corresponding grade correlations of Spirmen R not significantly. On the basis of one-factor parametrical and nonparametric analyses of variance the importance of heterogeneity of variables dt, ex and ihw on three streams is estimated: strongly significant for dt, insignificant for ex and highly significant for ihw on a population of 3 streams. Both criteria also are used at paired comparison of streams. The importance of heterogeneity of variables dt, ex and ihw on 10 groups is similarly estimated. Outcomes of the spent analysis of variance can be considered within the limits of passing reform of higher education.

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Михальчук А.А, Арефьев В.П, Филипенко Н.М СРАВНИТЕЛЬНЫЙ СТАТИСТИЧЕСКИЙ АНАЛИЗ ПАРАМЕТРИЧЕСКИХ И НЕПАРАМЕТРИЧЕСКИХ МЕТОДОВ ОЦЕНИВАНИЯ ЗНАНИЙ В СИСТЕМЕ ЗАОЧНОГО ОБУЧЕНИЯ // Научное обозрение. Физико-математические науки . 2020. № 1. С. 42-42;
URL: https://physics-mathematics.ru/en/article/view?id=53 (дата обращения: 24.06.2026).