Welcome to the InfoSci Platform
Reference Hub1
Data Visualisation and Statistics Education in the Future

Data Visualisation and Statistics Education in the Future

Theodosia Prodromou, Tim Dunne
Copyright: © 2017 |Pages: 28
ISBN13: 9781522525127|ISBN10: 1522525122|EISBN13: 9781522525134
DOI: 10.4018/978-1-5225-2512-7.ch001
Cite Chapter Cite Chapter

MLA

Prodromou, Theodosia, and Tim Dunne. "Data Visualisation and Statistics Education in the Future." Data Visualization and Statistical Literacy for Open and Big Data, edited by Theodosia Prodromou, IGI Global, 2017, pp. 1-28. https://doi.org/10.4018/978-1-5225-2512-7.ch001

APA

Prodromou, T. & Dunne, T. (2017). Data Visualisation and Statistics Education in the Future. In T. Prodromou (Ed.), Data Visualization and Statistical Literacy for Open and Big Data (pp. 1-28). IGI Global. https://doi.org/10.4018/978-1-5225-2512-7.ch001

Chicago

Prodromou, Theodosia, and Tim Dunne. "Data Visualisation and Statistics Education in the Future." In Data Visualization and Statistical Literacy for Open and Big Data, edited by Theodosia Prodromou, 1-28. Hershey, PA: IGI Global, 2017. https://doi.org/10.4018/978-1-5225-2512-7.ch001

Export Reference

Mendeley
Favorite

Abstract

Data visualisation has blossomed into a multidisciplinary research area, and a wide range of visualisation tools has been developed at an accelerated pace. Preliminary statistical data analysis benefits from data visualisation to form the basis for decision-making. There is a greater need for people to make good inferences from visualisations. The flexible nature of current computing tools can potentially have a major impact on the learning and practice of the discipline of statistics and allow easier use of visualisations in the educational process. While this view has many merits and we support its general spirit, we argue for a valuable role for a non-visual approach at certain points. Students will employ data visualisation in an OPEN Data context. This chapter is a theoretical discussion of a framework, which emphasises explicit assumptions that help to direct inferences appropriately. In particular it addresses the common illusions of causality in student reasoning. Our discussion of points of disagreement is based on specific theoretical concerns.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.