The course introduces the theory and practice of exploring, describing, summarizing and detecting patterns of interest in complex datasets. Various approaches including aggregation, clustering, data visualization, and latent variable modeling will be employed. This course will give students an opportunity to develop computational skills (primarily in R) and to learn how to discover and interpret relationships in unstructured observational data. The applications and examples for this course will be broad and relevant to many fields of study.
Offering: Host
Grading: A-F
Credits: 1.00
Gen Ed Area: NSM-QAC, SBS-QAC
Prereq: QAC211 OR ECON300 OR GOVT367