Implications of the data revolution for statistics education

Ridgway, Jim

doi:10.1111/insr.12110

Implications of the data revolution for statistics education

Ridgway, Jim

Authors

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

Abstract

There has never been a more exciting time to be involved in statistics. Emerging data sources provide new sorts of evidence, provoke new sorts of questions, make possible new sorts of answers and shape the ways that evidence is used to influence policy, public opinion and business practices. Significant developments include open data, big data, data visualisation and the rise of data-driven journalism. These developments are changing the nature of the evidence that is available, the ways in which it is presented and used and the skills needed for its interpretation. Educators should place less emphasis on small samples and linear models and more emphasis on large samples, multivariate description and data visualisation. Techniques used to analyse big data need to be taught. The increasing diversity of data usage requires deeper conceptual analysis in the curriculum; this should include explorations of the functions of modelling, and the politics of data and ethics. The data revolution can invigorate the existing curriculum by exemplifying the perils of biassed sampling, corruption of measures and modelling failures. Students need to learn to think statistically and to develop an aesthetic for data handling and modelling based on solving practical problems.

Citation

Ridgway, J. (2016). Implications of the data revolution for statistics education. International Statistical Review, 84(3), 528-549. https://doi.org/10.1111/insr.12110

Journal Article Type	Article
Acceptance Date	Jun 9, 2015
Online Publication Date	Jul 29, 2015
Publication Date	Dec 1, 2016
Deposit Date	Jun 9, 2015
Publicly Available Date	Jul 29, 2015
Journal	International Statistical Review
Print ISSN	0306-7734
Electronic ISSN	1751-5823
Publisher	Wiley
Peer Reviewed	Peer Reviewed
Volume	84
Issue	3
Pages	528-549
DOI	https://doi.org/10.1111/insr.12110
Keywords	Statistics education, Modelling, Open data, Big data, Visualisation, Data-driven journalism, Curriculum, Statistical literacy, Change.

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Advance online version © 2015 The Authors. International Statistical Review published by John Wiley & Sons Ltd on behalf of International Statistical Institute. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.