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Spring 2019 Quantitative Methods: Social Sciences GR5065 section 001
BAYESIAN STATS FOR THE SOC SCI
BAYESIAN STATS FOR THE SO

Call Number 73559
Day & Time
Location
TR 4:10pm-5:25pm
417 Mathematics Building
Points 4
Grading Mode Standard
Approvals Required None
Instructor Benjamin K Goodrich
Type SEMINAR
Method of Instruction Classroom
Course Description An introduction to Bayesian statistical methods with applications to the social sciences.  Considerable emphasis will be placed on regression modeling and model checking. The primary software used will be Stan, which students do not need to be familiar with in advance. Students in the course will access the Stan library via R, so some experience with R is necessary.  Any QMSS student is presumed to have sufficient background. Any non-QMSS students interested in taking this course should have a comparable background to a QMSS student in basic probability.  Topics to be covered are a review of calculus and probability, Bayesian principles, prediction and model checking, linear regression models, Bayesian calculations with Stan, hierarchical linear models, nonlinear regression models, missing data, and decision theory.
Web Site Vergil
Department Graduate School of Arts and Sciences
Enrollment 18 students (65 max) as of 12:16AM Tuesday, September 17, 2019
Status Full
Final Exam Day/Time
T 4:10pm-7:00pm
Final Location 405 International Affairs Building
Subject Quantitative Methods: Social Sciences
Number GR5065
Section 001
Division Graduate School of Arts and Sciences
Open To School of the Arts, Barnard, Columbia College, Engineering and Applied Science: Graduate, Graduate School of Arts and Science, General Studies, School of Professional Studies, Global Programs, International and Public Affairs, Public Health
Campus Morningside
Note QMSS MA Students Priority
Section key 20191QMSS5065G001

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