- Knowledge of statistical methods
- Prior knowledge of Stata but not mandatory
- Bring a laptop
- Professionals dealing with research and economic analysis.
- Undergraduate and graduate students
- Data scientists
- Instructor: admin
- Duration: 3 days
The aim of this course is to help participants increase their practical skills in using Stata for data analysis and regression. This course does not teach data analysis and regression (in a theoretical sense), per se, but focuses on how to practically perform data and regression analyses using Stata. Therefore, participants are expected to have prior theoretical knowledge of statistical methods covering topics such as descriptive and inferential statistics, with the latter including topics such as simple and multiple regression. Prior knowledge of Stata is also needed, though not mandatory. The course will cover several aspects related with importation of data, transformation of data, formulation, estimation and interpretation of a simple or multiple linear model, checking for outliers & influential data points and how to overcome these, performing the necessary diagnostic tests (normality, heteroskedasticity, linearity, model specification, multicollinearity and independence). In addition, the course shall explore regressions with categorical predictors, robust regression methods, constrained linear regressions, regressions with censored/truncated data, regressions with measurement error and multiple equation regression models (i.e. seemingly unrelated regressions and multivariate regression).