2018 Case Studies in Data Analysis Competition
The Case Studies in Data Analysis Competition will be held during the Annual Meeting at McGill University. The case studies are intended to provide enthusiastic teams of graduate and senior undergraduate students with the opportunity to apply their knowledge to the analysis of real-life datasets. Each participating team will choose to analyze one of the two case studies described below. Each team should identify a faculty member to support its members as they develop their analytic approach and final presentation. Team members will work together to analyze their data, and then present a poster summarizing their methods and analysis results at the Annual Meeting.
Further information about the case studies is available on the Annual Meeting website. Teams interested in participating in the competition must register by May 2, 2018 by e-mailing the Chair of the Case Studies in Data Analysis Committee, Dr. Lisa Lix (email@example.com).
Case Study 1: Does survey design information matter? Assessing the impact on population estimates of hypertension in Canada
Teams that select this case study will use synthetic data from the Canadian Health Measures Survey to assess the impact of using and not using survey design information when producing estimates of hypertension from this unique national health survey.
Case Study 2: What predicts the popularity of TED Talks?
Teams that select this case study will use data from the TED website to investigate characteristics that contribute to the popularity of motivational and inspirational talks on a variety of topics. This case study will require the use of a variety of tools to develop measures from text-based data and to analyze these data.
Criteria for Evaluating Case Study Entries
The Committee of the Award for Case Studies in Data Analysis will consider such attributes as innovation, technical clarity, and cohesiveness of the analysis and presentation of results in choosing a winning team for each competition. The Committee reserves the right to decline to make an award for each case study if the number of entries is insufficient.