Samuel Kou
STAT 120 | Fall 2024 | Course Listing | Canvas Site
Monday & Friday, 1:30 PM – 2:45 PM
Provides students a comprehensive understanding to the questions as of what is, how and why Bayesian. Introduction to classic Bayesian models, basic computational algorithms/methods for Bayesian inference, as well as their applications in various domain fields, and comparisons with classic Frequentist methods. As Bayesian inference finds its roots and merits particularly in application, this course puts great emphasis on enhancing students’ hands-on skills in statistical computation (mostly with R) and data analysis.
Recommended Prep: STAT110, STAT111 and basics of R programming are required.