QUANTITATIVE METHODS III
Syllabus
Aggiornato A.A. 2021-2022
Aggiornato A.A. 2021-2022
Attending students from the B.D. in Business Administration and Economics must have passed Quantitative Methods I and Quantitative Methods II (or similar courses). A good understanding of multiple linear regression models is mandatory.
Detailed of topics:
- Introduction to the R software
- Categorical data analysis: multi-way tables, distributions.
- Principles of causal analysis: selection, bias, confounding. Confounders, colliders, mediators. Simpson's Paradox
- Binary outcome regression models: Linear probability model, Logit and Probit.
- Multinomial ouctome regression: Multinomial Logit.
- Count outcome regression models: Poisson regression and Overdispersion.
- Instrumental Variables.
- Panel data models and estimators.
- Introduction to supervised learning: classification trees and random forests.