Statistical Probability and Scientific Certainty
A.Y. 2025/2026
Learning objectives
Undefined
Expected learning outcomes
Undefined
Lesson period: Second semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course can be attended as a single course.
Course syllabus and organization
Single session
Responsible
Lesson period
Second semester
Course syllabus
The first part of the course is dedicated to statistical tools for risk analysis: data and variables; time series and cross-sectional data; descriptive statistics; graphical representation of data; frequency distributions and summary measures (mean, variance, and standard deviation); probability, uncertainty, and risk; interpretation of data, construction of indicators, and limits of statistical evidence. indicators; limits of statistical evidence. The second part is dedicated to to the basic concepts of philosophy of science, with a focus on the use of scientific evidence in contexts of epistemic uncertainty: experimental and observational methodologies; scientific reasoning; logical fallacies and cognitive biases; operationalization and measurement practices; values in science.
Applications: illustrative examples may be drawn from credit risk assessment and firm evaluation, including sustainability and ESG factors; the impact of climate-related and geopolitical risks on credit risk and financial decision-making; and governance-related risks, including board diversity, gender gaps, and their relationship with ESG disclosure and greenwashing; public health, medicine and psychiatry; technological innovation.
Applications: illustrative examples may be drawn from credit risk assessment and firm evaluation, including sustainability and ESG factors; the impact of climate-related and geopolitical risks on credit risk and financial decision-making; and governance-related risks, including board diversity, gender gaps, and their relationship with ESG disclosure and greenwashing; public health, medicine and psychiatry; technological innovation.
Prerequisites for admission
The course has no specific prerequisites, except for a basic understanding of percentages, growth rates, working with datasets, using basic Excel functions, and fundamental financial concepts.
Teaching methods
PowerPoint presentations and Excel exercises.
Teaching Resources
Details will be given at the beginning of the course.
Assessment methods and Criteria
The exam aims to assess the achievement of the following learning objectives:
- Knowledge and understanding of the main theoretical concepts related to statistical tools, probability, uncertainty and risk.
- Ability to interpret and critically analyze economic, financial and business phenomena using basic statistical reasoning. - Ability to evaluate the role and limits of statistical evidence in decision-making processes, particularly in contexts characterized by uncertainty and ESG-related risks.
- Ability to analyze theoretical, practical and ethical problems through the specific gaze of the philosophy of science.
The exam consists of a written test.
- Knowledge and understanding of the main theoretical concepts related to statistical tools, probability, uncertainty and risk.
- Ability to interpret and critically analyze economic, financial and business phenomena using basic statistical reasoning. - Ability to evaluate the role and limits of statistical evidence in decision-making processes, particularly in contexts characterized by uncertainty and ESG-related risks.
- Ability to analyze theoretical, practical and ethical problems through the specific gaze of the philosophy of science.
The exam consists of a written test.
Modules or teaching units
Philosophy of Science
M-FIL/02 - LOGIC AND PHILOSOPHY OF SCIENCE - University credits: 3
Lessons: 21 hours
Professor:
Serpico Davide
Statistics
SECS-P/11 - FINANCIAL MARKETS AND INSTITUTIONS - University credits: 3
Lessons: 21 hours
Professor:
Brighi Paola
Professor(s)
Reception:
Tuesday 4.30 pm
Via Festa del Perdono 3