URL study guide
https://tue.osiris-student.nl/onderwijscatalogus/extern/cursus?cursuscode=JBM025&collegejaar=2026&taal=enDescription
- Potential outcomes model, treatment effects, experiments
- Selection on observables and matching
- Difference-in-difference estimation
- Regression discontinuity design
Objectives
After completing the course ‘Data Science Research Methods’ students will have learned to make use of (quasi-) experimental designs to estimate causal effects. Students will have learned which tools are called for by the different structures of data and the underlying reason for the analysis. They are able to critically assess the results they obtain themselves and results obtained by others.In particular,
• Students know the potential outcomes framework and can use it to define causal effects. They understand the link between the potential outcomes framework and regression analysis and can interpret regression coefficients as causal effects when appropriate.
• Students can formally describe the main econometric techniques for estimating causal effects.
• Students are able to interpret and evaluate estimation results.
• Students are able to analyze a provided data set using statistical software and interpret the results (application, analysis, evaluation).
• Students can reason which estimator can or cannot be used to answer a given question using data.