- Docente: Carmela Lardo
- Credits: 6
- Language: Italian
- Teaching Mode: Traditional lectures
- Campus: Bologna
- Corso: First cycle degree programme (L) in Mechatronics (cod. 6009)
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from Sep 16, 2024 to Dec 17, 2024
Learning outcomes
At the end of the laboratory course, the student knows the fundamentals of a numerical computation program and uses it to solve simple problems in calculus, linear algebra, and mathematical modeling. The student acquires proficiency with measurement instruments and error handling. Additionally, the student approaches numerical and statistical computation with professional rigor.
Course contents
- Introduction to Python
- Errors and error propagation
- Basics of statistics - Concepts and applications
- Univariate and bivariate descriptive statistics
- Measures of central tendency, dispersion, position and relationship between variables
- Discrete random variables
- Probability functions
- Binomial distribution
- Poisson distribution
- Continuous random variables
- Probability distributions
- The normal distribution
- The continuous uniform distribution
- The central limit theorem
- Sampling error
- Standard error
- Hypothesis testing
- Linear regression
Teaching methods
Lectures, with development of the theoretical part, simple python exercises in the lab.
Assessment methods
1. Writing a python programme for solving a physics and/or mathematics problem
2. Presentation of the programme
3. discussion of theoretical topics covered in the lectures
Teaching tools
Projector, python notebooks
Office hours
See the website of Carmela Lardo