Attention conservation notice: Notice of an advanced statistics class at a university you probably don't attend, covering abstruse topics you probably don't care about. Also, it's the first time the class is being offered, so those who do take it will have the fun of helping me debug it.
This course is an introduction to the opportunities and challenges of analyzing data from processes unfolding over space and time. It will cover basic descriptive statistics for spatial and temporal patterns; linear methods for interpolating, extrapolating, and smoothing spatio-temporal data; basic nonlinear modeling; and statistical inference with dependent observations. Class work will combine practical exercises in R, some mathematics of the underlying theory, and case studies analyzing real problems from various fields (economics, history, meteorology, ecology, etc.). Depending on available time and class interest, additional topics may include: statistics of Markov and hidden-Markov (state-space) models; statistics of point processes; simulation and simulation-based inference; agent-based modeling; dynamical systems theory.
Co-requisite: For undergraduates taking the course as 36-467, 36-401. For graduate students taking the course as 36-667, consent of the professor.
Course materials will be posted publicly on the class website (once that's up).
Posted at April 27, 2018 09:19 | permanent link