Study of the association in an insubordination way between qualitative and quantitative variables using Geogebra

Abstract

This paper studies the relevance of outlier detection in a data set when we seek to determine the association between qualitative and quantitative variables. The article is a piece of research developed for a PhD program in Science and Mathematics teaching, which aims, among its objectives, to evaluate the usability of GeoGebra software in the teaching and learning of Statistics in higher education courses, specifically in the courses. Engineering degree. Qualitative analysis using the case study was adopted as an investigation method, as the phenomenon under study is part of the context of students' academic life. A specific activity was developed to evaluate the relationship between qualitative and quantitative variables, with some moments of creative insubordination when choosing the data set to be analyzed and during the problem-solving process. Breaking with pre-established models in the way to approach and work statistical concepts, reflects the speech of D'Ambrosio and Lopes (2015), when they consider that the autonomy of the mathematics teacher is essential to characterize their professional identity, as it gives them the courage to engage in creative insubordination toward those who educate. In the course of the activity it was found the presence of significant amount of discrepant data due to the size of the data set under study, this fact motivated the discussion among students about the strong influence of outliers on the result of the statistical analysis. An important factor observed was that regardless of the hardware characteristics of the computers used during the experiment, it was possible to employ a significant amount of data lines, which allowed the practice of teaching and learning statistics.