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Data Visualisation and Statistics Education in the Future

Theodosia Prodromou, Tim Dunne

Research output: Chapter in Book/Report/Conference proceedingChapterResearchpeer-review

2 Citations (Scopus)

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.
Original languageEnglish
Title of host publicationData Visualization and Statistical Literacy for Open and Big Data
EditorsTheodosia Prodromou
Place of PublicationHershey, United States of America
PublisherIGI Global
Pages1-28
Edition1
ISBN (Print)9781522525134, 9781522525127
DOIs
Publication statusPublished - 2017

Keywords

  • Educational Technology and Computing
  • Technical, Further and Workplace Education
  • Education

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