Spring 2024 Quantitative Methods: Social Sciences GR5015 section 001

DATA ANALYSIS FOR THE SOCIAL SCIENCES

DATA ANALYSIS FOR THE SOC

Call Number 13143
Day & Time
Location
R 6:10pm-8:00pm
1102 International Affairs Building
Points 3
Grading Mode Standard
Approvals Required None
Instructor Mike Z He
Type LABORATORY
Method of Instruction In-Person
Course Description

Prerequisites: One semester of undergraduate statistics The data analysis course covers specific statistical tools used in social science research using the statistical program R. Topics to be covered include statistical data structures, and basic descriptives, regression models, multiple regression analysis, interactions, polynomials, Gauss-Markov assumptions and asymptotics, heteroskedasticity and diagnostics, models for binary outcomes, naive Bayes classifiers, models for ordered data, models for nominal data, first difference analysis, factor analysis, and a review of models that build upon OLS. Prerequisite: introductory statistics course that includes linear regression. There is a statistical computer lab session with this course: QMSS G4017 -001 -DATA ANALYSIS FOR SOC SCI

Web Site Vergil
Department Quantitative Methods/Social Sciences
Enrollment 23 students (25 max) as of 5:05PM Wednesday, July 24, 2024
Subject Quantitative Methods: Social Sciences
Number GR5015
Section 001
Division Graduate School of Arts and Sciences
Note PRIORITY QMSS STUDENTS
Section key 20241QMSS5015G001