Date:
March 17, 2021
Time:
3:00 - 4:00pm
Place:
Zoom - Registry Link Below
Researchers are often interested in performing an exploratory data analysis in order to generate hypotheses and then testing those hypotheses using the same data. Unfortunately, such "double dipping" can lead to highly-inflated Type 1 errors. Dr. Gao proposes a test for a difference in means between estimated clusters that solves the double dipping problem for clustering, using a selective inference framework.
Speaker: Lucy Gao, PhD, Assistant Professor of Statistics & Actuarial Science, Univ. of Waterloo
Register: http://eepurl.com/g1X35P
Event Type:
Biostatistics and Bioinformatics Seminar