COMPUTER, ELECTRONIC AND COMMUNICATIONS ENGINEERING

Professor: Tommaso FOGGI
Academic discipline: Telecomunicazioni (ING-INF/03)
Field: Ingegneria delle telecomunicazioni
Type of training activity: Characterising

48 hours
of face-to-face activities

6 credits

hub: PARMA

course unit
in ITALIAN

lectures timetable unavailable

exam calls

Learning objectives

Understanding and capability to communicate the foundation of probability theory. Capability to solve exercises on probability theory, to use the specific functions, to recognize and employ the random variable models studied during the course.

Prerequisites

Mathematical analysis

Course unit content

Introduction to descriptive statistics and inferential statistics. Elements of probability theory. Discrete and continuous random variables. Central limit theorem. Parameter estimation. Confidence intervals.

Full programme

Data organization e description, mean, median, mode, histograms, variance and standard deviation.
Normal model and correlation.
Sample space and events, probability axioms, binomial coefficient, conditional probability, Bayes' formula, independent events.
(approx. 6 hours)

Continuous and discrete random variables, probability density and cumulative functions, joint, conditional and marginal distributions, expected value, covariance, moment generating function. Random variables functions and transformations.
Random variable models: Bernoulli, Poisson, hypergeometric, binomial, uniform, normal, exponential, gamma, chi-square, t, F.
(approx. 24 hours)

Sample mean, central limit theorem, sample variance.
Maximum likelihood estimators, confidence intervals, bayesian estimators.
(approx. 18 hours)

Bibliography

Sheldon M. Ross
Introduction to probability and statistics for engineers and scientists
Elsevier, fifth edition, 2014.

A. Bononi, G. Ferrari
"Introduzione a Teoria della probabilità e aleatorie con applicazioni all'ingegneria e alle scienze"
Soc. Esculapio, Bologna, aprile 2008.

Teaching methods

Classroom lectures and exercises.
Homework exercises in autonomy.
Software use (Matlab) for problem resolution.

Assessment methods and criteria

Written exam with possible supplementary oral.

Other information

Classes will be held according to University instructions as regards the pandemic situation.

2030 agenda goals for sustainable development

- - -

Contacts

Toll-free number

800 904 084

Student registry office

E. segreteria.ingarc@unipr.it

Quality assurance office

Education manager:
Elena Roncai
T. +39 0521 903663
Office E. dia.didattica@unipr.it
Manager E. elena.roncai@unipr.it

PROBABILISTIC METHODS FOR ENGINEERING cod. 1010000

Learning objectives

Prerequisites

Course unit content

Full programme

Bibliography

Teaching methods

Assessment methods and criteria

Other information

2030 agenda goals for sustainable development

Contacts

Toll-free number

Student registry office

Quality assurance office

President of the degree course

Faculty advisor

Career guidance delegate

Tutor professor

Erasmus delegates

Quality assurance manager

Tutor students

PROBABILISTIC METHODS FOR ENGINEERING
cod. 1010000