S M A Statistical Methods & Applications Master Degree Laurea Magistrale last update March 6, 08 Master programme Data management and analysis, i.e. Statistics, is pervasive in any modern professional activity. SMA - Statistical Methods and Applications - is the acronym of the brand-new two-year Master of Science (in Italian Laurea Magistrale) 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 mi of advanced data modelling methodologies and hand-on professional training to address comple scientific and socio-economic problems. Students are prepared to handle the overall data management process: 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: [QE] Quantitative Economics [OS] Official Statistics (EMOS - European Master in Official Statistics label) [DA] Data Analyst (with optional path for Double Degree with Université Paris Dauphine) 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, Quantitative Economics and Econometrics, Data Science. Mandatory and elective courses are displayed in the following overview of the study plans. A more datailed list with credits, semester schedule and other constraints is available at http://corsidilaurea.uniroma.it/en. Students can alternatively submit their own individual study plan to the Master programme board. Piazzale Aldo Moro n. 5 0085 Roma https://www.uniroma.it/en/
Study Plan Overview Course_name DA_mandatory DA_elective OS_mandatory OS_elective QE_mandatory QE_elective Stochastic Processes Sample Theory Survey Methodology Advanced Statistical Data Analysis Spatial Statistics Bayesian Modelling Computational Statistics Statistical Learning Statistical Decisions Advanced Econometrics Algorithms and Data Structures Big Data Analytics Big Data for Official Statistics Efficiency and Productivity Analysis International Demography International Monetary Economics Applied Economics Development Finance Gender Economics Economic History Data management in Official Statistics Data quality and other issues in Official Statistics Advanced Economic Statistics Data Driven Decision Making Laboratory of Stochastic Processes Laboratory of Statistical Decisions Laboratory of Machine Learning Reading Seminars Seminars on Financial and Monetary Banking and Financial Statistics Statistical Consulting and Case Studies Internship Piazzale Aldo Moro n. 5 0085 Roma https://www.uniroma.it/en/
Selection process Selection process to enrol in the Statistical Methods and Applications Master programme requires: Academic background: at least an undergraduate (Bachelor) degree with a solid foundation in Calculus, Probability and Statistics, some computing skills and basic knowledge of programming. The academic background of international students (EU and non EU) is assessed by a Prospective Student Selection Committee based on the documentation provided by the student (see below). The Committee may also request an interview with the prospective student via Skype or other services. Italian candidates holding a Bachelor Degree in Statistics or Actuarial Sciences (Italian Laurea Degree L-4) are automatically accepted. Italian candidates with at least 60 ECTS in the subject areas corresponding to the Ministerial Scientific Sectors labelled as are automatically accepted. English language skills: The IELTS (International English Language Testing System) or TOEFL (Test of English as a Foreign Language) English Language proficiency certification. Note that certified minimum level B (within Common European Framework of Reference for Languages) or equivalent is required. English language level can be also ascertained during the preliminary remote (Skype) interview. Documentation: the following general documents about the university background of the candidate must be submitted: a transcript of records (list of eams, with material covered and grades obtained) The following documents, although not required, will constitute a positive element in the evaluation for admission to the SMA programme: Grade Point Average (GPA) and Cumulative-weighted Grade Point Average (CGPA) higher than 75% of its maimum GRE (Graduate Record Eaminations) General test, or Subject Tests in Math/Physics higher than 75% of its maimum up to two recommendation letters a motivation letter The pre-selection documentation must be submitted in electronic format via email at the following address sma-dss@uniroma.it. SMA selection stages The selection process for academic year 08/09 is formed by three phases with the following schedule: November, 07: pre-enrolment opens st selection phase April -5, 08: first selection phase. Letters of acceptance are sent to the best candidates who have applied till March, 08. Unselected applicants will be considered for the second selection phase. nd selection phase May -5, 08: second selection phase. Letters of acceptance are sent to the best candidates who have applied till April 0, 08 or who have not been selected in the first phase. rd selection phase June 6-0, 08: third selection phase. Letters of acceptance are sent to the best candidates who have applied till June 5, 08 or who have not been selected in the first and second phase. June 0, 08: pre-enrolment for non EU students closes. Piazzale Aldo Moro n. 5 0085 Roma https://www.uniroma.it/en/
July 6-, 08: Letters of acceptance are sent to the best candidates who have applied till July 5, 08. September 5, 08: pre-enrolment for EU students closes. Contacts For general information of pre-enrolment procedures send an email to Administration: sma-dss@uniroma.it You can also address more specific questions on the programme to: Prof. Fulvio De Santis [Master Programme Director]: fulvio.desantis@uniroma.it Prof. Stefano Fachin [QE curriculum]: stefano.fachin@uniroma.it Prof. Agostino Di Ciaccio [OS curriculum]: agostino.diciaccio@uniroma.it Prof. Luca Tardella [DA curriculum]: luca.tardella@uniroma.it Piazzale Aldo Moro n. 5 0085 Roma https://www.uniroma.it/en/ 4
Data Analyst curriculum course # credits Mandatory courses: 5 sector. Stochastic Processes 9 MAT/06. Statistical Decision Theory 9 SECS-S/0. Sample Theory 9 SECS-S/0 4. Advanced Economic Statistics 6 SECS-S/0 5. Advanced Statistical Data Analysis 9 SECS-S/0 6. Computational Statistics and Laboratory 9 SECS-S/0 Constrained elective courses: 4 7-0. choose 4 out of of the folllowing A. Bayesian Modelling 6 SECS-S/0 B. Big Data Analytics 6 SECS-S/0 - INF/0 C. Statistical Learning 6 SECS-S/0 D. Algorithms and Data Structures 6 INF/0 E. Spatial statistics 6 SECS-S/0 F. Data Driven Decision Making 6 MAT/09 G. Efficiency and productivity analysis 6 SECS-S/0 Free elective courses: -. freely choose two 6-credit eams Other credited activities: Laboratory of Stochastic Processes MAT/06 Laboratory of Statistical Decisions SECS-S/0 Laboratory of Statistical Consulting and Case Studies SECS-S/0 SECS-S/0 Laboratory of Machine Learning SECS-S/0 Final unit (thesis/project): year semester TOTAL credits to be earned 0 Piazzale Aldo Moro n. 5 0085 Roma https://www.uniroma.it/en/ 5
Official Statistics curriculum course # credits Mandatory courses: 5 sector. Stochastic Processes 9 MAT/06. Statistical Decisions 6 SECS-S/0. Data quality and other issues in Official Statistics 6 6 SECS-S/0 SECS-S/0 4. Data management in Official Statistics 6 SECS-S/0 5. Sample Theory 9 SECS-S/0 6. Advanced Statistical Data Analysis 9 SECS-S/0 7. Advanced Economic Statistics 6 SECS-S/0 Constrained elective courses: 5 8-9. choose out of of the folllowing F. International Demography 6 SECS-S/04 G. Data Driven Decision Making 6 MAT/09 H. Bayesian Modelling 6 SECS-S/0 I. Statistical Learning 6 SECS-S/0 L. Algorithms and Data Structures 6 INF/0 C. Advanced Econometrics 9 SECS-S/05 A. Spatial Statistics and Statistical Tools for Environmental Data 9 9 SECS-S/0 SECS-S/0 B. Big Data for Official Statistics 6 SECS-S/05 D. Survey Methodology 6 SECS-S/05?? E. Efficiency and productivity analysis 6 SECS-S/0 Free elective course: 9 0. freely choose one 9-credit eam freely choose Other mandatory credited activities: Internship 9 Seminars on Monetary and Financial Statistics SECS-S/0 SECS-S/0 Other elective credited activities: a. Laboratory of Stochastic Processes MAT/06 b. Laboratory of Statistical Decisions SECS-S/0 c. Laboratory of Machine Learning SECS-S/0 Final unit (thesis/project): 0 year semester TOTAL credits to be earned 0 Piazzale Aldo Moro n. 5 0085 Roma https://www.uniroma.it/en/ 6
Quantitative Economics curriculum course # credits Mandatory courses: 48 sector. Stochastic Processes 9 MAT/06. Advanced Statistical Data Analysis 9 SECS-S/0. Efficiency and productivity analysis 9 SECS-S/0 4. Sample Theory 6 SECS-S/0 5. Advanced Econometrics 9 SECS-S/05 6. Advanced Economic Statistics 6 SECS-S/0 Constrained elective courses: 6 7-8. choose out of of the folllowing A. Economic History 9 SECS-P/ B. International Monetary Economics 9 SECS-P/0 C. Applied Economics 9 SECS-P/0 Constrained elective courses: 6 9-. choose courses out of the following : D. Gender Economics 6 SECS-P/0 E. Development Finance 6 SECS-P/0 F. Algorithms and Data Structures 6 INF/0 G. Big Data Analytics 6 SECS-S/0 H. Computational Statistics 6 SECS-S/0 I. Bayesian Modelling 6 SECS-S/0 Free elective courses: 9. freely choose one 9-credit eam 9 Other credited activities: 6 Laboratory of Stochastic Processes MAT/06 Laboratory of Statistical Decisions SECS-S/0 Laboratory of Machine Learning SECS-S/0 Seminars on Monetary and Financial Statistics Reading Seminars Final unit (thesis/project): SECS-S/0 SECS-S/0 year semester TOTAL credits to be earned 0 Piazzale Aldo Moro n. 5 0085 Roma https://www.uniroma.it/en/ 7
Pre-selection Application All students applying for admission to Sapienza degree programmes that accept pre-selection applications should complete this process. Please note: the pre-application process does NOT replace or substitute the embassy-based pre-enrolment process for Non-EU students (see: Admissions) request a Student Login Code to access the on-line pre-selection application form http://www.uniroma.it/internazionale/incoming/registrationdegreeprogramme.asp Use the following link http://www.uniroma.it/internazionale/incoming/logindegree.asp to submit the on-line pre-selection application and upload the following documents. Copy of your passport (pdf). English language certificates (optional). Transcript of Records or Diploma Supplement (pdf) 4. Letters of Recommendation 5. Passport Photograph (see requirements below) Photo requirements Your passport photo must be: in color square sized inches (5 5 mm) taken in front of a plain white or off-white background taken in full-face view directly facing the camera with a neutral facial epression (preferred) or a natural smile, and with both eyes open Piazzale Aldo Moro n. 5 0085 Roma https://www.uniroma.it/en/ 8