Data Science for all: A stroll in the foothills

Ridgway, J.; Ridgway, R.; Nicholson, J.

Data Science for all: A stroll in the foothills

Ridgway, J.; Ridgway, R.; Nicholson, J.

Authors

Professor Jim Ridgway jim.ridgway@durham.ac.uk

Dr Rosemary Ridgway r.a.ridgway@durham.ac.uk
Associate Professor

J. Nicholson

Contributors

M. A. Sorto
Editor

A. White
Editor

L. Guyot
Editor

Abstract

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.

Citation

Ridgway, J., Ridgway, R., & Nicholson, J. (2018). Data Science for all: A stroll in the foothills. In M. . A. Sorto, A. White, & L. Guyot (Eds.), Looking back, looking forward : proceedings of the Tenth International Conference on Teaching Statistics (ICOTS10, July, 2018), Kyoto, Japan (1-6)

Conference Name	International Conference on Teaching Statistics
Conference Location	Kyoto, Japan.
Acceptance Date	Feb 15, 2018
Online Publication Date	Mar 25, 2018
Publication Date	Mar 25, 2018
Deposit Date	Oct 21, 2019
Publicly Available Date	Apr 26, 2020
Pages	1-6
Book Title	Looking back, looking forward : proceedings of the Tenth International Conference on Teaching Statistics (ICOTS10, July, 2018), Kyoto, Japan.
Public URL	https://durham-repository.worktribe.com/output/1141698
Publisher URL	https://iase-web.org/Conference_Proceedings.php?p=ICOTS_10_2018