Studying at the University of Verona
Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.
Study Plan
Queste informazioni sono destinate esclusivamente agli studenti e alle studentesse già iscritti a questo corso. Se sei un nuovo studente interessato all'immatricolazione, trovi le informazioni sul percorso di studi alla pagina del corso:
Laurea in Matematica applicata - Immatricolazione dal 2025/2026.The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.
1° Year
Modules | Credits | TAF | SSD |
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2° Year activated in the A.Y. 2012/2013
Modules | Credits | TAF | SSD |
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3° Year activated in the A.Y. 2013/2014
Modules | Credits | TAF | SSD |
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Uno da 12 cfu o due da 6 cfu tra i seguenti tre insegnamenti
Modules | Credits | TAF | SSD |
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Modules | Credits | TAF | SSD |
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Modules | Credits | TAF | SSD |
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Uno da 12 cfu o due da 6 cfu tra i seguenti tre insegnamenti
Modules | Credits | TAF | SSD |
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Legend | Type of training activity (TTA)
TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.
Econometrics (2013/2014)
Teaching code
4S01951
Teacher
Coordinator
Credits
6
Language
Italian
Scientific Disciplinary Sector (SSD)
MAT/06 - PROBABILITY AND STATISTICSSECS-P/05 - ECONOMETRICS
Period
I semestre dal Oct 1, 2013 al Jan 31, 2014.
Learning outcomes
Statistical tools and economic theory will be applied in order to provide students with competences and capabilities to understand and perform empirical analysis of economic phenomena. Empirical problems and applications will be discussed during the course to provide students with the tools and capabilities needed for the analysis of economic data.
Program
Review of statistical inference.
The linear regression model.
Estimation: ordinary least squares.
Inference and testing.
Model diagnostics.
Time series regression for economic and financial data.
Examination Methods
Written exam.