The reproducibility of scientific studies with small sample sizes has always been a concern.
But what about large sample sizes? How do we think about questions of reproducibility in this age of big data?
Diverse fields now draw on gigantic datasets that come from high throughput methods or social media use. Does big data pose unique challenges? What safeguards would foster replication for both big and small data studies? What blindspots are being neglected, making the results or inferences from scientific studies unreliable? This conference tackles these questions from an interdisciplinary vantage point with the aim of improving scientific methodology.
Register Here(Registration closes April 28)
Buehler-Martin Plenary Lecture: Hadley Wickham, RStudio, Stanford University, University of Auckland
Buehler-Martin Keynote Lecture: Roger Peng, Johns Hopkins Bloomberg School of Public Health
IRSA Distinguished Lecture: David Danks, Carnegie Mellon University
IRSA Distinguished Lecture: Sabina Leonelli, University of Exeter
MCPS Plenary Lecture: Edouard Machery, University of Pittsburgh
UMN Current Faculty, Staff, Students
- $25 - Paying with UMN Dept. Chartstring
- $50 - General (no chartstring)
Public Pricing (non-UMN)
- $60 - Student/Postdoc
- $75 - Academic Faculty/Staff, Government, or Nonprofit
- $150 - General Admission (not in previous categories)