2026 ASEE Annual Conference & Exposition

Engineering students play a pivotal role in the creation and enhancement of innovative products, manufacturing systems, and processes, necessitating a strong foundation in statistical methods. These methods offer engineers both descriptive and analytical tools to address variability in observed data. Despite the significance of statistics in engineering, it is often challenging for students to incorporate a comprehensive statistics course into their curricula due to other academic requirements. Consequently, many engineering programs lack dedicated courses in engineering statistics [1].
In response to this gap, our paper presents a unique approach that can be effectively delivered as a freshman engineering course. While the statistical techniques presented are foundational across various disciplines such as business, management, life sciences, and social sciences, our focus remains on catering to an engineering-oriented audience. This targeted approach aims to empower engineering students to harness statistics for a myriad of applications within their field.
One distinctive aspect of our proposed course is the utilization of Python, a freely available programming language widely embraced in all engineering disciplines. By employing Python, we not only provide an accessible and cost-effective alternative to licensed statistical packages but also extend a valuable advantage to students in developing countries who may face challenges accessing proprietary software.
This paper is conceptual in nature and focuses on course design, curricular integration, and instructional examples rather than reporting empirical learning outcomes.