22455 - Lab-based Course on Mechanics and Thermodynamics (M-Z)

Academic Year 2022/2023

  • Moduli: Sara Valentinetti (Modulo 1) Nicolò Jacazio (Modulo 2) Silvia Arcelli (Modulo 3) Silvia Arcelli (Modulo 4)
  • Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2) Traditional lectures (Modulo 3) Traditional lectures (Modulo 4)
  • Campus: Bologna
  • Corso: First cycle degree programme (L) in Physics (cod. 9244)

Learning outcomes

The purpose of this course is to provide an introduction to probability and statistics useful in the analysis of experimental data. Students are expected to be able to correctly measure physical quantities, analyse data taken during laboratory sessions and write short reports.

Course contents

The measure of physical quantities

the experimental method; the International System (SI) of units; the experimental uncertanties (statistical and systematic errors); the Gauss distribution; the maximum likelihood method for the estimation of the parameters of a distribution; linear fits; rejection of data; the Student distribution; confidence intervals and confidence levels; the binomial and poissoninan disrtibution; the chi2 test.

Introduction to data acquisition based on electronic devices and personal computer

sensors and transducers; analog and digital signals; resolution, amplification, code width.

Laboratory sessions

sample of data extracted from a Gaussian population and best gaussian fit; calibration of a thermocouple and best linear fit; conservation of momentum and of angular momentum; measure of the specific heat of copper; measure of the ratio of molar heats of air; measure of the Boltzmann constant with a Perrin-like experiments.

Readings/Bibliography

P. Fornasini "The uncertainty in physical measurements" Springer.

A. Filipponi "Introduzione alla fisica" Zanichelli.

J. R. Tayor "Introduzione all'analisi degli errori" (seconda edizione)
Zanichelli.

Teaching methods

Lectures and laboratory sessions.

Assessment methods

Written examination consisting of 3 exercises on statistical method and 1 exercise on ROOT data analysis framework.

Oral examination consisting on the discussion of one experience performed in the laboratory sessions and 2 questions on statistical theory.



Teaching tools

Slides

Office hours

See the website of Sara Valentinetti

See the website of Nicolò Jacazio

See the website of Silvia Arcelli

See the website of Silvia Arcelli

SDGs

Quality education Gender equality Reduced inequalities

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