2019 Course List for ESS MA in Social Science Data Analysis.

Classifications for courses eligible for MA in Social Science Data Analysis

Students can count a maximum of one introductory course toward their MA course requirement and it is compulsory to take a minimum of two advanced courses for the MA.

Introductory
Applying Regression
Introduction to Survey Data Analysis
Introduction to Quantitative Methods in R
Web Scraping and Data Management in R
Introduction to Statistics for Social Science Research with SPSS

Intermediate
Introduction to Quantitative Text Analysis
Introduction to Social Network Analysis
Introduction to Multilevel Models
Longitudinal Data Analysis
Beyond OLS: Categorical, Choice and Count Models
Machine Learning for Social Scientists
Data Analysis and Programming in Stata
Quantitative Data Analysis with R
Multilevel Models: Practical Applications
Panel Data Analysis for Comparative Research
Mixed Methods Research
Causal Inference and Experiments in the Social Sciences
Introduction to Bayesian Analysis
Quantitative Text Analysis
Factor Analysis & Structural Equation Modelling with MPLUS

Advanced
Adv. Survey Data Analysis & Survey Experiments
Advanced Methods for Social Media and Textual Data
Generalized Linear Models
Times-Series and Panel Models for Dynamic and Heterogeneous Processes
Designing Your Own Statistical Models Using Maximum Likelihood Estimation
Bayesian Analysis for the Social and Behavioural Sciences
Advanced Methods for Policy Analysis and Evaluation
Spatial Econometrics
Advanced Quantitative Data Analysis
Scaling Methods and Ideal Point Estimation
Advanced Machine Learning for Social Scientists