STATS 102A: Introduction to Computational Statistics with R

This course is an introduction to computational statistics through numerical methods and computationally intensive methods for statistical problems. Topics include statistical graphics, root finding, simulation, randomization testing, and bootstrapping. Covers intermediate to advanced programming with R.

STATS 184: Societal Impacts of Data

This course considers the impacts that data collected today have upon individuals and society. The rapid increase in the scale and types of data collected has impacted commerce and society in new ways.

STATS 202B: Matrix Algebra and Optimization

This course is a survey of computational methods that are especially useful for statistical analysis, with implementations in statistical package R. Topics include matrix analysis, multivariate regression, principal component analysis, multivariate analysis, and deterministic optimization methods.

STATS 202C: Monte Carlo Methods for Optimization

This course is a survey of Monte Carlo methods and numerical integration. Importance and rejection sampling. Sequential importance sampling. Markov chain Monte Carlo (MCMC) sampling techniques, with emphasis on Gibbs samplers and Metropolis/Hastings.

STATS C216/C116: Social Statistics

This course is designed for social sciences graduate students and advanced undergraduate students seeking training in data issues and methods employed in social sciences. The Bruin Learn course page is here.

STATS 218: Statistical Analysis of Networks

This course is a introduction to the analysis of social structure, conceived in terms of social relationships. Major concepts of social network theory and mathematical representation of social concepts such as role and position.