ID:
509013
Duration (hours):
60
CFU:
6
SSD:
FISICA SPERIMENTALE
Year:
2025
Overview
Date/time interval
Primo Semestre (22/09/2025 - 09/01/2026)
Syllabus
Course Objectives
The Data Analysis I course (first module of the Experimental Physics I course, 1st semester) aims to provide an introduction to the measurement methodology and to the basic techniques of data analysis, in order to familiarize the student with the basics of experimental method, in particular in order to the 2nd semester Laboratory (second module of the course).
The introductory concepts of probability theory and descriptive statistics are also introduced in a phenomenological way.
The introductory concepts of probability theory and descriptive statistics are also introduced in a phenomenological way.
Course Prerequisites
None
Teaching Methods
The course will take place through lectures (about 40 hours) and exercises on problems and calculation methods (about 20 hours), also in groups and with the involvement of students. It will also be accompanied by two simple experiments in laboratory (volume measurements, observations at microscopy) and some practical exercises with Excel (solving integrals by numerical way, graphics representation and linearisation of functions, generation of random numbers according to different distributions).
Assessment Methods
The exam consists of a written test, with problems and calculation exercises (usually, one exercise for each of the following topics: dimensional analysis, error propagation, graphical representation, probability, probability distributions) and some eventual brief questions of theory, and an oral exam on the program carried out in the lectures. Admission to the oral exam takes place with at least 15/30 in the written exam. Passing the Data Analysis exam is required for admission to the Physics Laboratory exam (2nd module of the Experimental Physics I course).
Texts
John Taylor, Introduzione all’analisi degli errori, (ed. Zanichelli).
G.Cannelli, Metodologie sperimentali in Fisica (ed. EdiSES).
Paolo Fornasini, The Uncertainty in Physical Measurements (ed. Springer).
Dapor-Ropele, Elaborazione dei dati sperimentali (ed. Springer).
The previous texts are recommended as references; the course slides will be provided via the UniPV Kiro platform, indicating the educational path followed and allowing the study also with the aid of the recommended texts.
G.Cannelli, Metodologie sperimentali in Fisica (ed. EdiSES).
Paolo Fornasini, The Uncertainty in Physical Measurements (ed. Springer).
Dapor-Ropele, Elaborazione dei dati sperimentali (ed. Springer).
The previous texts are recommended as references; the course slides will be provided via the UniPV Kiro platform, indicating the educational path followed and allowing the study also with the aid of the recommended texts.
Contents
Introductory notions. Numerical calculations: use of powers of 10 - approximate calculations and orders of magnitude - scientific notation - systems of units of measurement - dimensional equations and dimensional analysis - change of units of measurement.
Introduction to measurement. Direct, indirect and calibrated instrument measurements - accuracy and precision of a measurement - characteristics of measuring instruments.
Introduction to the study of uncertainties. Types of errors - expression of uncertainty - absolute and relative uncertainty - statistical analysis of random errors - propagation of uncertainties (for statistically independent measures).
Data processing techniques. Descriptive statistics: frequency distributions and histograms, central position and dispersion indices. Graphs and graphical analysis of data: variable changes, linearization, determination of the slope and intercept, functional scales, semi-logarithmic and bilogarithmic graphs - graphical interpolation, linear and from a table.
Introduction to probability. Sampling space and events - classical and frequentistic definition of probability - hints to the axiomatic definition - addition and multiplication of events and probabilities for compound events - conditional probability - reminder of combinatorics.
Distributions of random variables. Random variables - probability distributions for discrete and continuous variables - numerical characteristics of populations - binomial distribution - Poisson distribution - normal or Gauss distribution - Gauss approximation to binomial and Poisson distributions - uniform and triangular distribution.
Introduction to measurement. Direct, indirect and calibrated instrument measurements - accuracy and precision of a measurement - characteristics of measuring instruments.
Introduction to the study of uncertainties. Types of errors - expression of uncertainty - absolute and relative uncertainty - statistical analysis of random errors - propagation of uncertainties (for statistically independent measures).
Data processing techniques. Descriptive statistics: frequency distributions and histograms, central position and dispersion indices. Graphs and graphical analysis of data: variable changes, linearization, determination of the slope and intercept, functional scales, semi-logarithmic and bilogarithmic graphs - graphical interpolation, linear and from a table.
Introduction to probability. Sampling space and events - classical and frequentistic definition of probability - hints to the axiomatic definition - addition and multiplication of events and probabilities for compound events - conditional probability - reminder of combinatorics.
Distributions of random variables. Random variables - probability distributions for discrete and continuous variables - numerical characteristics of populations - binomial distribution - Poisson distribution - normal or Gauss distribution - Gauss approximation to binomial and Poisson distributions - uniform and triangular distribution.
Course Language
Italian
More information
Students for whom inclusive teaching is envisaged (see https://portale.unipv.it/it/didattica/servizi-lo-studente/modalita-didattiche-inclusive) are invited to contact the teacher, who will give them the video recordings of the 2021/22 course and all the teaching material, and will be able to organize any tutoring dedicated to them.
Degrees
Degrees
PHYSICS
Bachelor’s Degree
3 years
No Results Found