Programming for Statistical Science
Statistical programming, computation using selected languages and environments (Python, R, Matlab, and/or C/C++) and interfaces with custom code development for statistical models. Best practices and software development for reproducible results, selecting topics from: use of markup languages, understanding data structures, design of graphics, object oriented programming, vectorized code, scoping, documenting code, profiling and debugging, building modular code, and version control- all in contexts of specific applied statistical analyses. Instructor consent required. Prerequisite: Statistical Science 360, 601L, 602L, or 611 (or concurrent enrollment in any of these courses). Not open to students who have taken Statistical Science 323D.