DATA SCIENCE FOR POLICY DECISIONS Single channel

Chair (Coordinator) and Rapporteur: PIERPAOLO D'URSO

Lecturers

Objectives

Provide the theoretical foundations and essential tools of data science and exploratory statistical analysis for political decision-making.
Specifically:

Knowledge and Understanding
• Informational paradigm (information, knowledge, decision-making)
• Data science and exploratory statistical analysis
• Data matrix and data pre-processing
• Proximity matrix
• Covariance matrix and correlation matrix
• Cluster Analysis
• Principal Component Analysis
• Data-driven democracy
• Measuring democracy
• Indicators related to the democratic process

Applying Knowledge and Understanding
• Ability to select and apply the learned statistical methodologies to political processes and decisions

Autonomy of Judgment
• Independent ability to collect, process, and interpret data and results

Communication Skills
• Ability to clearly present the results of statistical analyses

Learning Skills
• Ability to independently learn new statistical techniques

Learning outcomes

Ability to independently learn new statistical techniques

Prerequisites

Basic statistics

Programme

• Informational paradigm (information, knowledge, decision-making)
• Data science and exploratory statistical analysis
• Data matrix and data pre-processing
• Proximity matrix
• Covariance matrix and correlation matrix
• Cluster Analysis
• Principal Component Analysis
• Data-driven democracy
• Measuring democracy
• Indicators related to the democratic process

Books

APPUNTI DEL DOCENTE

Lessons mode

Lectures, exercises.

Frequency

Strongly recommended attendance.

Exam mode

Written exam (exercises). The test is intended to assess knowledge and understanding and the student's ability to apply knowledge and understanding. In itinere evaluation will be performed, based on two tests with the same structure and rules.

  • Academic year2026/2027
  • Degree program to which the course belongsPolitical Sciences and International Security
  • Lesson code10628114
  • Year and semester1st year - 2nd semester
  • Activity typeAttività formative affini ed integrative
  • Academic areaAttività formative affini o integrative
  • SSDSTAT-01/A
  • Mandatory presenceNo
  • LanguageITA
  • CFU9 CFU
  • Total duration63 hours
  • Hours distribution63 classroom hours