- Docente: Laura Pasqualini
- Credits: 6
- Language: Italian
- Moduli: Laura Pasqualini (Modulo 1) Marco Corvo (Modulo 2)
- Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2)
- Campus: Bologna
- Corso: First cycle degree programme (L) in Mechatronics (cod. 6009)
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from Sep 15, 2025 to Oct 28, 2025
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from Nov 03, 2025 to Dec 16, 2025
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 Python modules to reproduce program topics: data fit and animations, probability calculation, visualization of statistical distributions, kinematics, thermodynamics and neural networks. The student will be guided on simulations of didactic experiences.
The student will also be able to build a laboratory project, autonomously.
Readings/Bibliography
During the course of the program, the material presented during the lessons will be made available in terms of slides in pdf format.
Books
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 the subjects showed during the lessons.
Exercises will be carried out by means of the Python tool called Jupyter Notebook, available with the suite Anaconda.
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 pfd format (possibly with the source file used to produce it, for example Latex, Word, PowerPoint etc., 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.
Furthermore, basic knowledge of the theoretical topics covered during the course will also be verified.
Students with DSA or temporary or permanent disabilities: it is recommended to contact the responsible University office in advance (https://site.unibo.it/studenti-con-disabilita-e-dsa/it): it will be their responsibility to propose any adaptations to the interested students, which must in any case be submitted, 15 days in advance, for the approval of the teacher, who will evaluate the opportunity also in relation to the educational objectives of the course
Teaching tools
All the lectures will be accompained with slides in pdf format that can be downloaded from the Virtuale website.
Office hours
See the website of Laura Pasqualini
See the website of Marco Corvo