Implications of the Data Revolution for Statistics Education

Abstract

SummaryThere 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.

Why We Should Teach Causal Inference: Examples in Linear Regression With Simulated Data

“…For some time now, there has been a call for the integration of causal inference in introductory statistics (or data science) courses (e.g., Ridgway 2016;Kaplan 2018;Hernán, Hsu, and Healy 2019;Cummiskey et al 2020). The Book of Why (Pearl and Mackenzie 2018) increased the motivation to teach concepts that Pearl calls the causal revolution, see, for example, the interview of JSE's editor Jeff Witmer (Rossman and Witmer 2019).…”

Chilean Children’s Reading Levels of Statistical Graphs

“…A relevant part of the information we face every day in the media is given in statistical graphs, whose interpretation is often needed to make different decisions in almost all areas linked to everyday and professional life. Therefore, there is a need for citizens to achieve enough graphical competence to manage in the information society (Ridgway, 2016). According to Aoyama (2007), citizens are increasingly dealing with statistical information presented through different graphs and an important role of statistical education in the 21st century is that citizens are able to ask critical questions about the information represented through graphs and obtain conclusions about this information.…”

Discussion: Locating Statistics in the World of Finding Out

“…A forthcoming article in the International Statistical Review by Jim Ridgway () is entitled, ‘ Implications of the data revolution for statistics education ’. As I write this, I am also drafting my discussion of a paper by George Cobb () entitled, ‘ Mere Renovation is Too Little Too Late: We need to rethink our undergraduate curriculum from the ground up ’ (to appear in The American Statistician ).…”