STATC131A

This course teaches a broad range of statistical methods that are used to solve data problems. Topics include group comparisons and ANOVA, standard parametric statistical models, multivariate data visualization, multiple linear regression, logistic regression and classification, regression trees and random forests. An important focus of the course is on statistical computing and reproducible statistical analysis. The course and lab include hands-on experience in analyzing real world data from the social, life, and physical sciences. The R statistical language is used.

Course is not repeatable for credit.

DATA/COMPSCI/INFO/STAT C8 or STAT 20; and MATH 1A, MATH 51, MATH 16A, or MATH 10A/10B. Strongly recommended corequisite: STAT 33A or STAT 133.