Statistical Computing. 3 credits

Catalog description

Introduces modern and basic elements of statistical computing. Topics include: data wrangling, numerical computation for statisticians, semi-numerical computation (simulation methodology and algorithms), graphical computation, and special topics in resampling, Bayesian calculations, mixtures, EM algorithms, parallel processing, and some modern data analytics (time permitting). Some complex programming problems related to statistical modeling and inference are studied. R and its interfaces with other programming languages will be used. (Other types of programming languages are allowed with the permission of instructor). Offered by Statistics . May not be repeated for credit.