DATA ANALYSIS

Academic year
2025/2026 Syllabus of previous years
Official course title
DATA ANALYSIS
Course code
FOY28 (AF:600971 AR:338371)
Teaching language
English
Modality
On campus classes
ECTS credits
5
Subdivision
A
Degree level
Corso di Formazione (DM270)
Academic Discipline
NN
Period
2nd Semester
Course year
1
Where
VENEZIA
Moodle
Go to Moodle page
In today's data-driven world, the ability to extract valuable insights from large and complex datasets is highly relevant after across various fields and disciplines. The DATA ANALYSIS course aims to provide students with with a solid background on the main concepts and techniques to effectively analise data and extract valuable information.
The course aims to provide students with a general overview of some of the main aspects of data analysis, through theoretical lectures, exercises, and programming in Python.
Students are expected to have some basic understanding of the mathematical concepts of variable and function. Moreover, students are expected to have good computer utilisation skills.
The course will cover the following topics:
- Descriptive statistics (mean, median, variance, standard deviation)
- Covariance and the Pearson correlation coefficient
- Significant figures and rounding
- Distributions: uniform, binomial, Poisson, Gaussian
- Central Limit Theorem
- Error propagation
- Conditional probability and Bayes’ theorem
- Python programming with Google Colab
Statistics: A Guide to the Use of Statistical Methods in the Physical Sciences, by R. J. Barlow, Publisher: Wiley, 1993
The final grade will be a weighted average of the following components:
- 10% class attendance
- 40% mid-term exam
- 50% final exam
written
The following is the grading on the basis of a maximum of 30L
18–21 points: Given for weak comprehension and underdeveloped problem-solving skills.
22–25 points: Indicates good comprehension and solid problem-solving techniques.
26–27 points: Reflects very good understanding and problem-solving ability.
28–30L points: Awarded for excellent performance.
Theoretical lectures, practical exercises, and Python programming sessions.
Definitive programme.
Last update of the programme: 17/01/2026