Academic Year 2023/2024

  • Moduli: Alessandro Gabrielli (Modulo 1) Carmela Lardo (Modulo 2) Carmela Lardo (Modulo 3)
  • Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2) Traditional lectures (Modulo 3)
  • Campus: Bologna
  • Corso: First cycle degree programme (L) in Mechatronics (cod. 6009)

Learning outcomes

At the end of the laboratory the student knows the fundamentals of a symbolic and numerical calculation program and uses it to solve simple calculus problems, linear algebra and mathematical modeling. The student acquires dexterity with the measuring instruments and the handling of errors. Furthermore, he approaches numerical and statistical calculation with professional rigor.

Course contents

Laboratory module

Theory - Introduction to the theory of measures; error propagation; random fluctuations and systematic effects; precision and accuracy; evaluation of the uncertainty of a result; Gauss distribution; binomial and Poisson distribution; linear correlation; notes on probability theory; statistical distributions; rejection of experimental measures.

Laboratory tests

Various experiences with Phyton modules to reproduce program topics: data fit and animations. The student will be guided on simulations of didactic experiences

The student will also be able to build a laboratory project, autonomously.


During the course of the program, the material presented during the lessons will be made available in terms of slides in pdf format.


- FISICA per Scienze ed Ingegneria - Quinta Edizione

Serway Jewett - EdiSES edizioni - due volumi

- A.Bertin, M. Poli, A. Vitale, Fondamenti di Termodinamica, Esculapio Editore (Progetto Leonardo), Bologna

- J. R. Tayor "Introduzione all'analisi degli errori" Zanichelli.

Teaching methods

Lectures and laboratory experiences with Python simulations. A part of the lessons is dedicated to the discussion of questions and exercises in Mechanics and Statistics. The student must know how to use the sw tools to study the exercises (for this he will be guided by a didactic tutor)

Assessment methods

Verification of learning is by project. In particular, it consists of a mandatory oral discussion aimed at evaluating the work presented which, in turn, consists of the following parts:

- a project in Python language on a mathematics or physics topic carried out in class,

- a report in Jupyter Notebook format with the description of the work done,

- a presentation slide file in pdf or ppt format used for the common presentation in front of all the students of the course,

The project must be agreed in advance with the teacher.

Teaching tools

All the lectures will be accompained with slides in pdf format that can be downloaded from the Virtuale site

Office hours

See the website of Alessandro Gabrielli

See the website of Carmela Lardo

See the website of Carmela Lardo


Quality education Industry, innovation and infrastructure

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.