On Understanding Statistical Data Analysis in Higher Education

TL;DR

This paper discusses the importance of integrated statistical data analysis skills in higher education physics courses, proposing a learning path focused on nuclear phenomena to develop these competencies through practical experiments and data analysis.

Contribution

It introduces a structured learning path that combines theoretical knowledge and practical data analysis in nuclear physics to enhance interdisciplinary scientific skills.

Findings

Students can monitor natural radioactivity over time.

Data analysis enhances understanding of nuclear phenomena.

Practical experiments improve statistical competence in physics.

Abstract

Data analysis is a powerful tool in all experimental sciences. Statistical methods, such as sampling theory, computer technologies necessary for handling large amounts of data, skill in analysing information contained in different types of graphs are all competences necessary for achieving an in-depth data analysis. In higher education, these topics are usually fragmentized in different courses, the interdisciplinary integration can lack, some caution in the use of these topics can missing or be misunderstood. Students are often obliged to acquire these skills by themselves during the preparation of the final experimental thesis. A proposal for a learning path on nuclear phenomena is presented in order to develop these scientific competences in physics courses. An introduction to radioactivity and nuclear phenomenology is followed by measurements of natural radioactivity. Background and weak sources can be monitored for long time in a physics laboratory. The data are collected and analyzed in a computer lab in order to understand the importance of statistical analysis in a not trivial case.