Applied Statistics

Teacher: Giovanni C. PORZIO
Credit ETCS: 10
Weeks: 20
Hours weekly: 4
Status: Mandatory
Quarter: I-II

R.D. Cook & S. Weisberg (1999). Applied Regression Including Computing and Graphics. New York: Wiley
S. Weisberg (2005). Applied Linear Regression, third edition. New York: Wiley.

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 willl be devoted to applications and case studies.

Simple Linear Regression. Multiple Regression. Weighted regression and Lack of Fit. Polynomial Regression. Regression with categorical predictors. Transformations. Regression Diagnostics: Residuals, Outliers and Influence. Nonconstant Variance. Variance Stabilizing Transformations. Graphs for Model Assessment. Variable Selection. Nonlinear Regression. Binary response regression. Structural Equation Models and their applications.

Exams and Grading:
Written + oral final exam.