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Data Visualisation and Statistics Education in the Future
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.
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