A Computational Framework for Teaching Statistical Moments Using Maple and R

Abstract

Many scientific topics remain confined to a theoretical framework, with limited connection to practical applications. This is due to several factors, most notably the large of data, the complexity of manual computational processes, and the high level of accuracy required in results, which often exceeds ordinary human capabilities. Statistics education is one of the fields that faces this challenge, particularly in the topic of statistical moments. This research paper aims to develop an instructional approach in teaching and learning statistics by describing data using statistical moments, through the integration of advanced computational tools. Specifically, the study utilizes Maple within Computer Algebra Systems (CAS), and R as an interactive environment for statistical computing. The study adopts a combined theoretical and applied methodology. The theoretical part presents the algebraic formulas of statistical moments, while the practical part includes computational applications using the mentioned software. This approach seeks to simplify concepts and facilitate their application in a practical and accessible manner for both teachers and learners.