Being able to choose the most appropriate statistical model for the analysis of socio-economic phenomena. Getting familiar with the statistical environment R for model estimation and goodness of fit evaluation. Being able to communicate efficiently the model output.
teacher profile teaching materials
Mutuazione: 21801968 MODELLI STATISTICI in Scienze politiche e relazioni internazionali L-36 LAGONA FRANCESCO
Programme
Introduction to R e R Studio. Importing data. Basic graphs. Basics of descriptive data analysis. Linear models: analysis of variance and regression. Interactions and transformations, Generalized linear models: logistic regression and Poisson regression. Time series analysis: temporal autocorrelation and linear models with ARMA errors. Spatial statistics: spatial autocorrelation and linear models with SAR and CAR errors. Panel data: random effects and generalized linear mixed effects models.Core Documentation
Dalgaard, P (2008) Introductory Statistics with R, Springer.Type of delivery of the course
The course includes lectures and labs.Attendance
Attendance is highly recommended but not mandatory.Type of evaluation
The exam consists of the defence of a project paper that includes the statistical analysis of a dataset. The work must rely on the statistical methods and models have have been presented during the course. The choice of the dataset is free but it must be approved by the instructor. During the period june-july 2020, due to the pandemic crisis, the defence will take place electronically thorugh the E-Teams platform.