Unit LABORATORY IST
- Course
- Fisica
- Study-unit Code
- GP005447
- Curriculum
- In all curricula
- Teacher
- Aniello Grado
- Teachers
-
- Aniello Grado
- Stefano Germani (Codocenza)
- Hours
- 58 ore - Aniello Grado
- 42 ore (Codocenza) - Stefano Germani
- CFU
- 10
- Course Regulation
- Coorte 2025
- Offered
- 2025/26
- Learning activities
- Caratterizzante
- Area
- Sperimentale e applicativo
- Academic discipline
- FIS/01
- Type of study-unit
- Obbligatorio (Required)
- Type of learning activities
- Attività formativa monodisciplinare
- Language of instruction
- Italian
- Contents
- Systems of units, fundamental units - Errors of measurement - functional relationships - graphs. Systematic and statistical errors - Statistical Distributions Lab experiences related to the course of Fisica I.
- Reference texts
- .R. Taylor, Introduzione all'analisi degli errori, Zanichelli, Bologna M. Severi, Introduzione alla sperimentazione fisica, Zanichelli, Bologna and additional resources.
- Educational objectives
- Measurement methods, interpretation of the results and formulation of physical laws from experimental data analysis.
- Prerequisites
- There are no specific additional skills needed. First year student are expected to have a basic high school preparation.
- Teaching methods
- Lessons and labs activities.
- Other information
- none
- Learning verification modality
- The assessment takes place in two phases: 1. A written test aimed at verifying the knowledge of statistical data processing. 2. Reports - the working groups prepare, based on the experimental activities carried out in the laboratory, a report in which the experience is described and the results are discussed. Optional oral test - preparation and acquired skills are assessed by discussing in detail the contents of the reports produced and the written test on statistical data processing.
- Extended program
- Measurement unit systems, fundamental quantities - Measurement errors - Functional relationships between physical quantities - Graphs. Random and systematic errors - Statistical distributions - Least squares - Statistical tests - Introduction to Bayesian statistics - Use of the Python programming language applied to statistical data processing. Laboratory experiments complementing the Physics I course.