Pursuing a career in the field of applied statistics and data analytics: What are the antecedents?

Abstract

Gaining insight into the interests of individuals in a particular job position or field of specialisation is crucial for educators, decision-makers, and policymakers when guiding them in pursuing their desired professional careers. This is especially important in job positions related to STEM (science, technology, engineering, mathematics), as these fields have global impact, influencing economies, societies, and the environment. Considering the advances of machine learning, artificial intelligence and open innovation, on one side, and traditional fear and anxiety towards mathematics-related subjects, understanding the factors that impact the students` decision to pursue a career in the field of applied statistics and data analytics is important not only for the future job market but for the future of teaching and lecturing statistics. To scrutinise the latter statement, the authors surveyed undergraduates' attitudes towards specialising in statistics and data analytics. A total of 401 responses were acquired independently from two consecutive generations. Logistic regression models were developed for both covered generations. Regarding the results, firstly, both models were noted as statistically significant. Secondly, classification success ranges from 71.3% for the 2022/23 generation to 81.5% for the current generation (2023/24). Thirdly, the model for the previous generation outlined high expectations of programming skills and a prosperous perspective of data analytics as significant predictors. On the contrary, the current generation model showed that the undergraduate program and a prosperous data analytics perspective are significant predictors. Furthermore, gender and grades in mathematical subjects showed no statistically significant relevance to model prediction. This study sheds light on the fact that students' interest in specialising in the fields of statistics and applied statistics did not change between generations. However, the factors impacting their decision-making have. Studies such as this could act as an impetus for further, more detailed studies on tracking undergraduates' perception of the field of statistics as a potential career path.