Statistical programming in a high-level language, data visualization design principles, extracting insights from data visualization, data mining and machine learning, data classification; visualization of multivariate, time-series, and hierarchical data. Currently using R including ggplot2 and other relevant packages.

Antirequisite(s): Statistical Sciences 2864A/B.

Prerequisite(s): 1.0 from Economics 2222A/B, Economics 2223A/B, Statistical Sciences 2035, Statistical Sciences 2857A/B, Statistical Sciences 2858A/B; or 1.0 credits from Psychology 2840F/G, Psychology 3891F/G, Psychology 3892F/G, Sociology 2205A/B, Sociology 2206A/B; or by permission of the department.

Extra Information: 3 lecture hours, 2 lab hours.