SMA - Statistical Methods and Applications

Word CloudJoy PlotRunning Time SeriesBubble MapWord CloudJoy PlotRunning Time SeriesBubble Map(**)


Information on each course can be found at the corresponding page in
Highlight #1 :: Courses timetable

Highlight #2 :: Access to electronic library resources

Highlight #3 :: Italian for foreign students

Highlight #4 :: The form to apply for Double Degrees is available 

Highlight #5 :: The 4th International Data Analysis Olympiad is now on: Join the competition

SMA - Statistical Methods and Applications - is the acronym of the brand-new two-year Master of Science (corresponding to the Italian Laurea Magistrale degree) entirely taught in English and delivered by the Department of Statistical Science (DSS). DSS is the largest Department of Statistics in Italy and its faculty members enjoy international reputation in teaching and research. DSS hosts one of the most powerful computing resources at Sapienza University of Rome. The Master programme is entirely held in English. It provides students with specific statistical skills through a suitable mix of advanced data modelling methodologies and hand-on professional training to address complex scientific and socio-economic problems.

Students are prepared to handle the overall data management process: planning, collection, analysis, interpretation, decision making. Specific attention is devoted to methods for Big Data Analysis and their applications to relevant domains with a specific emphasis on economic phenomena. Starting from a common base of Statistics, Probability and Computing, the Master programme aims at delivering a solid and highly marketable statistical and quantitative training in the interpretation of real-world phenomena and support of decision-making.

Students can choose one of the following study plans:

All these three study plans (curricula) prepare professionals for careers in consulting companies, industry and State agencies as well as candidates for PhD programmes in Statistics, Data Science, Quantitative Economics and Econometrics.

(**) Credits and Acknowledgemet - The plots are downloaded form the R Graph Gallery <>. Creators of the logos are: Conor Healy: <> and Yan Holtz.