This paper is from Session 3A: Developing undergraduate data science programs grounded in statistics
which comes under Topic 3: Statistics education at the post-secondary level
Paper 3A1 (Tuesday 10th, 14:00-15:30)
Data Science for all: A stroll in the foothills
- Jim Ridgway (Durham University, United Kingdom)
- James Nicholson (University of Durham, United Kingdom)
- Rosie Ridgway (University of Durham, United Kingdom)
Data science presents both opportunities and threats to conventional statistics courses. Opportunities include being at the bleeding edge of data analysis, and learning new ways to model phenomena; threats include the challenge of learning new skills and reviewing fundamental assumptions about explanation, prediction and modeling. Powerful data visualisations makes it easier to introduce students to fundamental statistical ideas associated with multivariate data. Data science provides methods to tackle problems that are intractable using analytic methods. Students need to learn how to model complex problems, and to understand the problematic nature of modeling – and they need to consider the practical and ethical implications of their (and others’) work. Here, we offer a stroll into the foothills, along with aphorisms and heuristics for data analysts.