Advanced Statistical Programming Camp (ASPC)
The Advanced Statistical Programming Camp builds on the introductory statistical programming camp by expanding the computing toolsets of researchers. The camp shows how to analyze big datasets (e.g., voter files across many states, micro-level international trade data, large federal personnel databases) and employ computationally intensive methods (e.g., Monte Carlo simulations, Bayesian Markov chain Monte Carlo, cross-validation, or bootstrap).
We begin by introducing some low-cost strategies for improving performance in R. To help process large data and improve the speed of computation, we then cover parallel execution of R code on both personal machines and on remote high performance computing systems available at Princeton. Lastly, we cover basic C++ and the use of Rcpp to produce tightly integrated and fast compiled code.
For a detailed overview of information and materials, see here.
POL 245: Visualizing Data
The new Princeton University course POL 245: Visualizing Data with (co-developed with Kosuke Imai) has been offered during the summers 2013 and 2014 at Princeton University as part of the Freshmen Scholars Institute.
More information on the course is here.
For information pertaining to previous teaching duties in various capacities at The University of Rochester, see here.