Data Visualization: Bringing Data to Life in an Introductory Statistics Course

Lynette Hudiburgh & Diana Garbinsky

Journal of Statistics and Data Science Education2020https://doi.org/10.1080/10691898.2020.1796399article
ABDC B
Weight
0.56

What the paper says

Although the use of tables, graphs, and figures to summarize information has long existed, the advent of the big data era and improved computing power has brought renewed attention to the field of data visualization. As such, it is crucial that introductory statistics courses train students to become critical authors and consumers of data visualizations. To that end, we have developed a semester-long, instructor-supported, group project that exposes students to this growing field. We have found this project to be an exciting and effective way to teach students the power of statistics and, more importantly, the critical role context plays when interpreting statistics. Among the many benefits of this project are hands-on learning, improved mathematical reasoning, and better collaboration and communication skills. In this article, we describe the project structure, project assessment, and techniques for facilitating effective group work.

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https://doi.org/https://doi.org/10.1080/10691898.2020.1796399

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@article{lynette2020,
  title        = {{Data Visualization: Bringing Data to Life in an Introductory Statistics Course}},
  author       = {Lynette Hudiburgh & Diana Garbinsky},
  journal      = {Journal of Statistics and Data Science Education},
  year         = {2020},
  doi          = {https://doi.org/https://doi.org/10.1080/10691898.2020.1796399},
}

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Evidence weight

0.56

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.54 × 0.4 = 0.22
M · momentum0.80 × 0.15 = 0.12
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.