Advanced data analysis

A.A. 2022/2023
Crediti massimi
Ore totali
Obiettivi formativi
The purpose of this course is to introduce students to basic programming in Stata and to provide guidance on data management strategies for socio-economics data. The course will focus on command-based programming for modifying and managing data and performing statistical analysis in Stata.
Risultati apprendimento attesi
By the end of the course students will be able to comfortably navigate the Stata environment, create simple datasets, access existing datasets, create variables, use graphing functions, run commands to calculate summary statistics as well as inferential statistics, including simple and multiple regression.
Programma e organizzazione didattica

Edizione unica

Secondo trimestre

Introduction to Stata
· Data management
· Working with Data
· Bivariate Analysis and Hypothesis testing
· Graphics
· Simple Reression
· Multiple Regression
· Regression Diagnostics
· Non linear Regression
· Robust Regression
Mathematics and Statistics
Metodi didattici
The students will use a computer during the lectures. Every session will intermix the presentation of syllabus topics followed by examples and in class exercises. Optional group work will be offered to get familiar with the software and increase practical skills.
Materiale di riferimento
Hamilton, L. C., Statistics with STATA: Version 12, 8th Edition, Cengage, 2012 (Chapter 1,2,3,5,6,7,8)
· Stock J., Watson M. (2010) Introduction to Econometrics, 3rd Edition, Addison-Wesley, Pearson (Chapters 6,7,8,9)
· Additional materials (slides, exercises, example) in the ARIEL website
Modalità di verifica dell’apprendimento e criteri di valutazione
The exam consists in a project assignment and brief oral discussion.
The project will involve identifying a dataset, developing research questions, and using the skills learned in the class to answer the research questions. It will include a brief introduction, a methods section, a section on results, graphic representations of the sample and/or results, and a brief discussion. All assignments must be submitted via email (dataset, script, and pdf), they will be checked for plagiarism via During the oral discussion students must present the project and discuss the results.
Informatica di base: 20 ore
Docente: Salini Silvia
Siti didattici
Il ricevimento studenti e in presenza, per appuntamento, il martedi dalle 10.30 alle 12 e via Teams, per appuntamento, il venerdi dalle 10.30 alle 12.00.
DEMM, stanza 30, 3? p