Course program
The aim of this course is to provide students with some logical and technical statistical tools which may be exploited to tackle economics and business issues starting from data. The exploratory data analysis and model building perspective is adopted. Room is devoted to applications and case studies.
Course contents
Basics of statistical inference. Simple Linear Regression. Multiple Regression. Weighted regression. Polynomial Regression. Regression with categorical predictors. Dummy variables. Transformations. Regression Diagnostics: Residuals, Outliers and Influence. Nonconstant Variance. Variance Stabilizing Transformations. Graphs for Model Assessment. Variable Selection. Nonlinear Regression. Binary response regression. Experimental and observational studies/variables.
