Section outline

  • Fundamental and applied statistics - Prof. Elena Fabrizi - a.a. 2026/2027

    Elena Fabrizi is Associate Professor of Economic Statistics (SECS-S/03) at the University of Teramo, where over the years she has taught several courses in statistics and economic statistics. She is the Programme Director of the Bachelor's Degree in Business Management (L-18).

    She graduated in Economic Statistics at Sapienza University of Rome, where she also obtained her PhD in Economic Statistics.

    Her research focuses mainly on topics of applied economic analysis, such as the labour market, well-being and quality of life, using innovative databases that allow the observation of individual working careers enriched with survey information. Particular attention has been devoted to the process of producing and disseminating statistical information based on the analysis of large administrative databases (data warehouses).

    She has collaborated with the Italian Ministry of Economy and Finance (MEF) on the implementation of the Treasury Department's microsimulation model T-DYMM, providing econometric estimates related to demographic and labour market dynamics.

    Winner, together with Prof. Giuseppe Costa, of the VisitINPS research call for the estimation of differential mortality using INPS population databases.

    Until October 2020 she was the Italian delegate to the European Commission's Economic Policy Committee Working Group on Ageing Populations and Sustainability (AWG) (https://europa.eu/epc/working-group-ageing-populations-and-sustainability_en).

    2017–2020: Official at the MEF, Directorate I – Economic and Financial Analysis and Planning, Office II – Sustainability analysis, potential growth and structural balances.

    2016–2017: Official at AIFA, the Italian Medicines Agency (Ministry of Health), working on the control of Italian pharmaceutical expenditure through expenditure monitoring and payback procedures, and on the creation, management and development of the OsMed database and the registry of medicines marketed in Italy.

    Fundamental and Applied Statistics
    Bachelor's Degree in Business Management (L-18) – Year 1
    AY 2026/2027
    Elena Fabrizi

    Course programme

    The course provides an introduction to statistical methods and their application to economic and business analysis. SAS programming is used as the primary computational tool for practical applications throughout all parts of the programme.

    Part 0 – Statistical Reasoning: Counterfactual Analysis

    Part I – Descriptive Statistics and Probability
    1. Statistical data and types of variables
    2. Frequency distributions
    3. Measures of central tendency and variability
    4. Correlation, regression and counterfactual analysis
    5. Introduction to probability
    6. Random variables and probability distributions
    Lab: step-by-step SAS programming – basics, data input and dataset management

    Part II – Statistical Inference
    7. Sampling methods and basic concepts of statistical inference
    8. Point estimation and confidence intervals
    9. Introduction to hypothesis testing
    Lab: SAS programming – inference procedures

    Part III – Applications
    10. Correlation analysis and interpretation
    11. Linear regression and economic applications.
    Lab: SAS programming for applications in economic statistics; reporting and communicating results from SAS output

    Suggested bibliography

    Course textbook:

    * Fabrizi, E. (2026). Fundamental and Applied Statistics. Course textbook.

    * Sheldon M. Ross. Introductory Statistics . Academic Press.
    https://www.sciencedirect.com/book/monograph/9780443438905/introductory-statistics

    * Course materials provided by SAS Institute.

    Other reference textbooks: 
    * https://openstax.org/details/books/introductory-statistics-2e

    * Spiegelhalter, David.  The Art of Statistics: How to Learn from Data (New York, NY: Basic Books)  ISBN 978-1541618510.

    * Mann, P. S. (2019). Introductory Statistics. Wiley. ISBN 978-1-119-49782-4.

    * Newbold, P., Carlson, W. L., & Thorne, B. (2020). Statistics for Business and Economics. Pearson.

    * Stock, J. H., & Watson, M. W. (2020). Introduction to Econometrics. Pearson (selected chapters, for Part III).

    * Pituch, K. A., & Stevens, J. P. (2016). Applied Multivariate Statistics for the Social Sciences: Analyses with SAS and IBM's SPSS (6th ed.). Routledge. ISBN 978-0-415-83666-1

    Lecture slides, lecture notes, datasets, exercises and links to official statistical sources (e.g. Istat, Eurostat, OECD) are published in the corresponding sections of this page and updated during the semester. The final examination programme is defined by the materials and topics explicitly indicated on this page.

    SAS labs and SAS Academic Specialization

    The SAS labs are an integral part of the course. The course is part of the SAS Academic Specialization in Data Analysis for Business Management: students who pass the Fundamental and Applied Statistics exam are awarded the SAS Open Badge and are prepared for the official SAS Certification examination offered by SAS Institute.

    Continuous assessment: at the end of each part of the programme, in-class tests will be organised, open to all interested students. Students are also expected to prepare a short term paper (data analysis project in SAS). Midterm tests and the term paper contribute to the final grade.

    Final exam: a written exam is compulsory and does not constitute a prerequisite for the oral examination. Evaluation criteria include accuracy of answers, clarity of reasoning, correct use of statistical terminology, and the ability to interpret results in an economic context.

    Lectures start on Tuesday 27 October 2026, according to the following timetable:

    Tuesday 10.30–12.30 – blended, Computer Room 13
    Wednesday 10.30–12.30 – blended, Computer Room 13
    Thursday 10.30–12.30 – blended, Computer Room 13
    Friday 10.30–12.30 – online only, recorded

    Blended: the lecture takes place in the classroom and is streamed online at the same time. Online only: the lecture is delivered exclusively online. Recorded lectures are made available on this page.

    All times are Italian time (CET, UTC+1, from Sunday 25 October 2026). Students attending online from other time zones are advised to check the corresponding local time.

    Office hours, by appointment, can be held in person (Tuesday, Wednesday and Thursday) or online (Monday to Friday):
    in person: lecturer's office, Political Sciences wing, first floor, opposite side to the Dean's office
    online: on Google Meet, in the virtual classroom of the course
    (https://meet.google.com/eof-nbwk-eek)

    To book an appointment, write to efabrizi@unite.it.