Rigorous data collection and analysis
Originally Aired: 19th June 2017
To protect themselves against invalid conclusions, researchers need to take some straightforward steps to keep data collection and analysis in order.
Straightforward, that is, if researchers know about them ahead of time. Three experts in experimental design and analysis describe common pitfalls and how to avoid them. Topics include when to use p-values and when to avoid them, how and when to use the concept of statistical power to test for treatment effects, and how to include clever controls to rule out alternative hypotheses.
Professor of Biostatics and Division Chief, Biostatistics and Epidemiology
Weill Cornell Medical College
Executive Director, Age Related Disorders and Pathways
Novartis Institutes for BioMedical Research (NIBR)