20.560 Statistics for Biological Engineering
Provides basic tools for analyzing experimental data, interpreting statistical reports in the literature, and reasoning under uncertain situations. Topics include probability theory, statistical tests, data exploration, Bayesian statistics, and machine learning. Emphasizes discussion and hands-on learning. Experience with MATLAB, Python, or R recommended.
This class has no prerequisites.
20.560 will not be offered this semester. It will be available during IAP.
This class counts for a total of 4 credits. This is a graduate-level class.
You can find more information at the Paul Blainey, PhD site.
© Copyright 2015 Yasyf Mohamedali