92987 - BASIC ANALYTICS (1) (LM)

Conoscenze e abilità da conseguire

techniques concerning the analysis of data bases. In particular the student is expected to learn: - probability s tools - measures of variance - index numbers

Contenuti

Module A: Trapin

1. Data collection, management and visualization
   
   
2. Descriptive statistics
   
   
3. Foundations of probability
   
   
4. Statistical inference
   --> Sampling
   --> Estimation
   --> Hypothesis testing

 

Module B: Montalto (GIOCA students)

This 10-hour module is designed to equip future cultural managers and policy-makers with the foundational tools and understanding to engage effectively with data analysts and navigate the growing field of cultural data. Recognizing the increasing role of evidence-based decision-making in cultural policy, the course introduces students to key concepts, classifications, methods, and data sources used to measure culture — a complex and multidimensional domain.

Rather than training students to become data scientists, this course empowers them to ask the right questions, critically interpret statistical information, and use data to support or challenge cultural policy choices. Emphasis is placed on the practical use of data analytics for policy formulation, including the preparation, analysis, and visualization of data. Students will explore the limitations and potential of data in cultural measurement, helping them to manage uncertainty and make informed decisions in their future careers.

Topics include:

• Introduction: Why Data Matters in Cultural Policy

• Measuring Culture: Is That Even Possible?

• Data for Policy-Making: Purposes and Pitfalls

• Finding Reliable Data Sources

• Preparing, Analyzing, and Visualizing Cultural Data

By the end of the course, students will be better prepared to interpret cultural data, understand its relevance for policy, and engage thoughtfully in data-informed policy discussions in the cultural and creative sectors.

Testi/Bibliografia

Textbook

Luca Trapin, Lecture Notes for Basics Analytics.

Additional Material (Optional)

Gary Smith, Essential Statistics, Regression, and Econometrics, Academic Press (Elsevier).

David Spiegelhalter, The Art of Statistics: Learning from Data, Pelican Book.

Metodi didattici

Class lessons

Modalità di verifica e valutazione dell'apprendimento

Module A: Trapin

Written exam on EOL in Computer Lab: 20 multiple choice questions

1. 13 theoretical  
2. 7 excercises

The exam lasts one hour.

Grading system:

• <18: fail
• 18-23:sufficient
• 24-27: good
• 28-30: very good
• 30 e lode: excellent

Module B: Montalto (GIOCA students)

Attendace required

 

Strumenti a supporto della didattica

Class notes on Virtuale

Orario di ricevimento

Consulta il sito web di Luca Trapin