SSC 2019 - Case Studies in Data Analysis Competition
The Case Studies in Data Analysis Poster Competition will be held during the Annual Meeting at the University of Calgary. 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 big datasets. Each participating team will choose to analyze one of the two data sets described below. Each team is strongly encouraged to identify a faculty member to support the members as they develop their analytic approach and final presentation. Team members will work together to present a poster summarizing their methods and analysis results at the Annual Meeting.
Teams that select this case study will use synthetic microscopic imaging data from the Broad Bioimage Benchmark Collection to develop statistical machine learning methods to predict the number of cell counts in the images.
Teams that select this case study will use real data from Canadian Community Health Survey (CCHS) to first create an ‘analytic dataset’ (combining from cycles 1.1, 2.1 and 3.1), and then use that dataset to estimate crude and adjusted measures of association between osteoarthritis and self-reported heart diseases.
The Committee of the Award for Case Studies in Data Analysis will consider such attributes as result accuracy, innovation of the analysis methods, technical clarity, and cohesiveness of the analysis, interpretation 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.
Teams interested in participating in the competition must register by April 15, 2019, by e-mailing the Chair of the Case Studies in Data Analysis Committee, Pingzhao Hu (Pingzhao.email@example.com).
Many thanks to members of the 2019 Case Studies in Data Analysis Committee for their contributions:
Ehsan Karim, School of Population and Public Health, University of British Columbia
Kathryn Morrison, Precision Analytics Inc. and McGill University
Chel Hee Lee, Critical Care Medicine, Alberta Health Services & University of Calgary
and other individuals: François Brisebois (Methodology Branch, Statistics Canada) and Qian Liu, University of Manitoba.