https://at-ceu.studyguide.timeedit.net/modules/ECBS5145?type=CORECourse title ECBS 5145 -Data Analysis 2 - Pattern discovery and regression analysisInstructor Tímea Laura MolnárEmail
[email protected] Office A509 on QS 5th floorOffice Hours TBATeaching Assistant PhD Candidate Zsuzsanna Vadle (
[email protected])(Optional) TA Discussion Group//Office Hours: time and venue TBACredits 2 US credits (4 ECTS credits)Module Mandatory in: 1st-year in MA in Economics, Data, and Policy (EDP) program; Elective in: 4th-year in Bachelor of Arts in Philosophy, Politics and Economics (PPE) and 4th-year in Data Science and Society (DSS) programsTerm and Time Fall 2 term in AY 2025-2026Course level MasterPrerequisites ECBS5138 Data Analysis 1 - Exploration Uncovering patterns in the data can be an important goal in itself, and it is the prerequisite to establishing cause and effect and carrying out predictions. The course starts with simple regression analysis, the method that compares expected y for different values of x to learn the patterns of mean dependence between the two variables. It discusses nonparametric regressions and focuses on the linear regression. It builds on simple linear regression and goes on to enriching it with nonlinear functional forms, generalizing from a particular dataset to other data it represents, adding more explanatory variables, etc. We also cover regression analysis for binary dependent variables, as well as nonlinear models such as logit and probit. We will discuss selected case studies in lectures, and interpretation and coding solutions will both be discussed using STATA.