First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Science
MATHEMATICS
Course unit
INTRODUCTION TO STOCHASTIC PROCESSES
SCO2046352, A.A. 2015/16

Information concerning the students who enrolled in A.Y. 2015/16

Information on the course unit
Degree course Second cycle degree in
MATHEMATICS
SC1172, Degree course structure A.Y. 2011/12, A.Y. 2015/16
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Degree course track GENERALE [010PD]
Number of ECTS credits allocated 8.0
Type of assessment Mark
Course unit English denomination INTRODUCTION TO STOCHASTIC PROCESSES
Website of the academic structure http://matematica.scienze.unipd.it/2015/laurea_magistrale
Department of reference Department of Mathematics
Mandatory attendance No
Language of instruction English
Branch PADOVA
Single Course unit The Course unit can be attended under the option Single Course unit attendance
Optional Course unit The Course unit can be chosen as Optional Course unit

Lecturers
Teacher in charge CARLES ROVIRA ESCOFET

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Core courses MAT/06 Probability and Mathematical Statistics 8.0

Course unit organization
Period Second semester
Year 1st Year
Teaching method frontal

Type of hours Credits Teaching
hours
Hours of
Individual study
Shifts
Lecture 8.0 64 136.0 No turn

Calendar
Start of activities 01/03/2016
End of activities 15/06/2016
Show course schedule 2019/20 Reg.2011 course timetable

Examination board
Board From To Members of the board
2 Introduzione ai Processi Stocastici - a.a. 2015/2016 01/10/2015 30/09/2016 ROVIRA ESCOFET CARLES (Presidente)
FERRANTE MARCO (Membro Effettivo)
CALLEGARO GIORGIA (Supplente)
DAI PRA PAOLO (Supplente)
FISCHER MARKUS (Supplente)

Syllabus
Prerequisites: A basic course in Probability
Target skills and knowledge: Good knowledge of the theory of the Poisson Process and the continuous time Markov processes. Ability to solve also advanced problems and exercises related to these processes.
Examination methods: Written examination
Assessment criteria: Homeworks (10%) - Final Exam (90%)
Course unit contents: Definition and properties of a stochastic process.
A discrete example: the Branching Process.
Poisson process: main properties and applications. Extensions to other Point Processes.
Continuous-time Markov Processes: definition and basic properties.
Queueing Theory: basic examples and main results.
Renewal Theory: definitions, main properties and examples.
Planned learning activities and teaching methods: Taught lessons: theory (32 hours) exercises (32 hours)
Textbooks (and optional supplementary readings)
  • Resnick, Sidney I., Adventures in stochastic processesSidney Resnick. Boston \etc.!: Birkhauser, --.