What a CSAIL grad student moonlighting as a newspaper reporter learned about statistics
, MIT CSAIL
Date: Friday, October 11, 2013
Time: 12:00 PM to 1:00 PM Note: all times are in the Eastern Time Zone
Host: Gerald Jay Sussman, MIT CSAIL
Contact: Marisol Diaz, email@example.com
Speaker URL: None
TALK: What a CSAIL grad student moonlighting as a newspaper reporter learned about statistics
In 2007, an academic cardiologist downloaded 42 medical studies from the Web site of drug giant GlaxoSmithKline, combined them in a meta-analysis, and found that the world's best-selling diabetes drug caused heart attacks. GSK lost about $12 billion in sales and market value. But a different way to analyze the same data -- a "Bayesian" way -- finds that the drug actually reduces heart attacks.
Or does it? We often hear of this conflict, between Bayesian and "frequentist" statistics. But much of the conflict is misguided. Viewed formally, on the same axes, the two schools of statistics turn out to share a tight symmetry. Criticisms of each can be transformed into a corresponding criticism of the other. I'll also show results from a new numerical algorithm that calculates the performance of "exact" hypothesis tests that hadn't previously been tractable to characterize. This algorithm has found unexpected behavior in the best such methods to date (calculated by tools like StatXact), and suggests a path forward that borrows from digital filter design.
Keith Winstein is a graduate student in CSAIL. From 2007 to 2010, he worked as a Staff Reporter at The Wall Street Journal, covering science and medicine.
Created by Marisol Diaz at Friday, October 11, 2013 at 2:18 PM.