Impact of Knowledge in Linear Algebra on Academic Performance in Quantitative Optimization Methods: A Data Analytical Approach

Abstract

The study focuses on the importance of linear algebra prerequisites for performance in the optimization subject in industrial engineering students. It is highlighted that mastery of linear algebra is essential to understand and solve complex engineering problems. The fundamental reasons that justify the relevance of this analysis are examined, such as the improvement of the curricular framework, decision-making on curricular advancement, improvement of student performance and alignment with the needs of the labor market. The methodology of the study includes the selection of a sample of students who took both subjects, the definition of relevant variables and the statistical analysis to evaluate the relationship between performance in linear algebra and optimization. A logistic regression will be applied to predict the probability of success in the optimization subject based on various variables.