Lecture on January 25, 2016; 4:00pm to 5:00pm; 3110 Etcheverry Hall at Berkely Institute of Data Science. What does it mean to work reproducibly and transparently? Why bother? Whom does it benefit, and how? What will it cost me? What work habits will I need to change? Will I need to learn new tools? What resources help? What's the simplest thing I can do to make my work more reproducible? How can I move my discipline, my institution, and science as a whole towards reproducibility?
The topics of scientific rigor and data reproducibility have been increasingly covered in the scientific and mainstream media, and are being addressed by publishers, professional organizations, and funding agencies, including NIH. This webinar – the first in a series titled Training Modules to Enhance Data Reproducibility (TMEDR) – will address topics of scientific rigor as they pertain to pre-clinical neuroscience research.
We need mathematical help to tell the difference between a real discovery and the illusion of one. Fellow of the Royal Society and future President of the Royal Statistical Society, Sir David Spiegelhalter visits Dr Nicole Janz to discuss reproducibility in scientific publications.