DATA ANALYSIS AND DATA MINING

Channel 1
LUCA SALVATI Lecturers' profile

Program - Frequency - Exams

Course program
1. General intro. 2. Operational Data mining. 3. Data base theory and big data. 4. Operational principles of multivariate statistics and data interpretation; Software for multivariate statistics. 5. Factor analysis and principal component analysis. 6. Cluster analysis. 7. Metric and non-metric multi-dimensional scaling (MDS). 8. Correspondence analysis and Canonical correlation analysis (CCA). 9. Regression analysis
Prerequisites
Linear algebra; Descriptive and inferential statistics
Books
Class notes (Google Drive) Theory: Maialetti M. - Sateriano A. (2024). Analisi esplorativa dei dati. CISU, Roma (ultima edizione). Exercises and examples: Anzalone F.M - Maialetti M. - Salvati L. (2024). I territori del PNRR. Applicazioni economiche con indicatori statistici CISU, Roma. Reading of a third book is compulsory for remote students: Salvati L. (2024). Statistica, economia e sostenibilità. Indicatori per l'analisi regionale. Franco Angeli, Milano. Free softwares for exercises.
Teaching mode
Class lesson. Laboratory with software.
Frequency
Class frequency
Exam mode
Written and oral; partial evaluations are possible during the class term; lab/project works allowed alone or in team
Bibliography
The same of above
Lesson mode
Class lesson. Laboratory with software.
  • Lesson code10592615
  • Academic year2025/2026
  • CourseCorporate strategy and governance
  • CurriculumStrategia aziendale - Business Management
  • Year1st year
  • Semester2nd semester
  • SSDSECS-S/01
  • CFU9
  • Subject areaDiscipline Statistiche e Matematiche