Department of Economics “Marco Biagi” (UNIMORE)
Course type: Master Degree Course
6 ECTS – Economic Statistics (SSD: STAT/02-A)
Semester: Second
Course objectives
This course provides students with the fundamental statistical toolkit required to navigate the complexities of modern business environments. By blending theoretical rigor with hands-on practice using SPSS/PSPP, students will learn to transform raw data into actionable managerial insights.
Course content
For each credit (ECTS) there are 7 hours of lectures and 18 hours of self-study by students. Thus, 1 CFU is equivalent to a standard study commitment of 25 hours.
- Preliminary concepts
- Measurement and scales
- Primary data collection and survey design
- Sample survey
- Sampling techniques and sample weights
- Data preparation, z-scores and outliers
- Two mean comparison test (t-test) and one-way ANOVA
- Measures of association (Chi-square)
- Covariance, correlation and rank correlation
- Bivariate and multiple linear regression
- Logistic regression
- Factor Analysis and Principal Component Analysis
- Clustering techniques: hierarchical and non-hierarchical
Teaching methods
Teaching is in-person and delivered in Italian. The teaching method is based on (a) face-to-face lectures with both theoretical and applied content, supported by teaching materials (slides, exercises, etc.) and lecture recordings; (b) exercises and demonstrations of the use of SPSS statistical software for dataset analysis, aimed at developing the ability to apply the knowledge acquired. Supplementary teaching materials (slides, exercises, sample exam papers, etc.) can be found on the course’s MS Teams/Moodle pages. In line with Course of Study decisions, lecture materials and video recordings will be made available mid-course. Streaming, however, is not permitted, in accordance with UNIMORE’s teaching delivery regulations.
Expected results
- Knowledge and understanding: Acquisition of statistical research principles, from sampling techniques to multivariate methods like PCA and clustering. Students will master the theoretical foundations required to analyze complex relationships between variables.
- Applying knowledge and understanding: Ability to conduct full-scale statistical investigations on real economic and financial data using SPSS/PSPP. Students will learn to select appropriate methodologies to transform raw data into business-ready reports and visualizations.
- Making judgments: Development of a critical approach to verify findings through rigorous statistical and economic theory. The course fosters the ability to self-assess analytical skills and ensure the soundness of drawn conclusions.
- Communication skills: Mastery in presenting statistical theories and empirical results with technical precision and coherence. Students will be able to deliver complex findings in professional written and digital formats for managerial stakeholders.
- Learning ability: Consolidation of statistical expertise as a permanent asset for independent empirical analysis. Students will develop the agility to autonomously update their skills in future professional or academic environments.
Final examination
Students have the flexibility to choose between two assessment methods: a final written exam or a group project to be presented on the exam date.
Materials and books
• [ENG] Mario Mazzocchi (2008). Statistics for Marketing and Consumer Research. London: SAGE. Chapters: 1, 3, 4, 5, 7, 8, 9, 10, 12. • [ITA] Zani S., Cerioli A. (2007). Analisi dei dati e data mining per le decisioni aziendali. Giuffrè Editore (ISBN: 8814136955). Chapters: 1, 2, 3, 4, 5, 6, 8, 9. • Slides and exercises from MS Teams/Moodle.