Mathematical modeling of local socioeconomic phenomena with GeoGebra and INEC data
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This article proposes a methodology for mathematical modeling of local socioeconomic phenomena, integrating the dynamic geometry software GeoGebra with public databases from Ecuador's National Institute of Statistics and Census (INEC). The research adopts a mixed methods approach with a descriptive and correlational scope. Socioeconomic variables such as employment rates, poverty levels measured by unsatisfied basic needs, consumer price indices, and business dynamics at the cantonal and provincial levels were selected. From these variables, linear, polynomial, and exponential regression models were constructed using the statistical analysis tools built into GeoGebra. The results show that GeoGebra enables dynamic and interactive visualization of the relationships among socioeconomic variables, facilitating the comprehension of trends, correlations, and behavioral patterns in real data. The models obtained had coefficients of determination (R²) above 0.85 in most cases analyzed, suggesting an acceptable fit for educational and exploratory analysis purposes. It is concluded that combining official statistical data with open access technological tools constitutes a valuable pedagogical resource for contextualized mathematics education and for the applied analysis of socioeconomic phenomena in local contexts.
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