Kolmogorov-Smirnov test for two large samples with two-tailed samples
Abstract
The problem investigated arose from the identification of persistent deficiencies in doctoral theses, master's degrees, and diploma theses related to hypothesis validation. The objective of this work was to show how to validate a hypothesis using the nonparametric Kolmogorov-Smirnov test for large, two-tailed samples. The master's thesis of the main author of this work was used as a reference, through which the criteria of 140 randomly selected teachers from the Technical and Vocational Education Department in the province of Holguín and 35 experts from across the country were validated. This made it possible to determine whether there was concordance in relation to the evaluations issued by these teachers, related to the dimensions and indicators for assessing the educational impact of the Industrial Polytechnic Schools of said province (proposed by the author). As a result, it was established, with 95% confidence, that the evaluative criteria for each indicator issued by the experts were consistent with the criteria expressed by the teachers of the Technical and Vocational Education Department in the province of Holguín, which made it possible to validate, with a greater degree of confidence, the relevance of the hypothesis posed in the thesis. It can be concluded that this work demonstrates in a practical way how to apply this valuable tool that enables the validation of research hypotheses
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