The students learn about the basic models used to represent cross-sectional and time series data. The main objective is the interpretation of the models with less emphasis on technical aspects. There is also a focus on the empirical implementation of the models. The students not only learn about the models but also implement them to analyse real data.
The first part of the course deals with the regression model. In particular, the students learn about the Ordinary Least Squares estimation of the parameters and the diagnosis of the asumptions of the model. In the second part of the course, the basic models to represent the evolution of the conditional means of time series are described. The students learn how to fit and forecast using seasonal ARIMA models.