Fall 2023 Statistics GR6103 section 001

APPLIED STATISTICS III

Call Number 13412
Day & Time
Location
TR 10:10am-11:25am
903 School of Social Work
Points 4
Grading Mode Standard
Approvals Required None
Instructor Bianca Dumitrascu
Type LECTURE
Method of Instruction In-Person
Course Description Prerequisites: STAT GR6102 Modern Bayesian methods offer an amazing toolbox for solving science and engineering problems. We will go through the book Bayesian Data Analysis and do applied statistical modeling using Stan, using R (or Python or Julia if you prefer) to preprocess the data and postprocess the analysis. We will also discuss the relevant theory and get to open questions in model building, computing, evaluation, and expansion. The course is intended for students who want to do applied statistics and also those who are interested in working on statistics research problems.
Web Site Vergil
Department Statistics
Enrollment 11 students (25 max) as of 9:07PM Wednesday, May 1, 2024
Subject Statistics
Number GR6103
Section 001
Division Graduate School of Arts and Sciences
Open To GSAS
Campus Morningside
Note STAT PhD students only.
Section key 20233STAT6103G001