MAN 610 Data Analytics and Statistics
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The main purpose of the course is to develop knowledge skills and abilities concerning the fundamentals in econometric modelling, prediction based methods, and machine learning. In each class session, specific techniques will be introduced and then we will examine research papers published in different fields of business and economics that have applied the techniques introduced. In the first part of the class, emphasis will be placed on techniques that bolster claims of causality, including instrumental variables, fixed effects regression, natural experiments, propensity score matching and regression discontinuity design. Second part of the course will introduce students to the fundamental theories and concepts used for prediction and machine learning techniques (e.g. maximum likelihood estimation, classification, clustering methods, regression trees, and ensemble methods).
Credit units: 3 ECTS Credit units: 5.
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