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.

Karla Ballman, PhD
Professor of Biostatics and Division Chief, Biostatistics and Epidemiology
Weill Cornell Medical College
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Marcus Munafò, PhD
Professor of Biological Psychology
University of Bristol
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David J. Glass, M.D.
Executive Director, Age Related Disorders and Pathways
Novartis Institutes for BioMedical Research (NIBR)
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Monya Baker
Correspondent and Editor, Reproducibility
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