First cycle degree courses Second cycledegree courses Single cycledegree courses School of Science STATISTICS FOR ECONOMICS AND BUSINESS
Course unit
INTRODUCTION TO PROBABILITY (Ult. numero di matricola pari)
SCP4063485, A.A. 2017/18

Information concerning the students who enrolled in A.Y. 2017/18

Information on the course unit
Degree course Number of ECTS credits allocated First cycle degree in STATISTICS FOR ECONOMICS AND BUSINESS SC2095, Degree course structure A.Y. 2014/15, A.Y. 2017/18 bring this pagewith you 9.0 Mark INTRODUCTION TO PROBABILITY http://scienzestatistiche.scienze.unipd.it/2017/laurea_statisticaeconomiaimpresa Department of Statistical Sciences https://elearning.unipd.it/stat/course/view.php?idnumber=2017-SC2095-000ZZ-2017-SCP4063485-PARI No Italian PADOVA The Course unit can be attended under the option Single Course unit attendance The Course unit can be chosen as Optional Course unit

Lecturers
Teacher in charge Other lecturers DAVID BARBATO MAT/06 MARKUS FISCHER MAT/06

Mutuating
Course unit code Course unit name Teacher in charge Degree course code
SCP4063485 INTRODUCTION TO PROBABILITY (Ult. numero di matricola pari) DAVID BARBATO SC2094

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Basic courses MAT/06 Probability and Mathematical Statistics 9.0

Course unit organization
Period Second semester 1st Year frontal

Type of hours Credits Teaching
hours
Hours of
Individual study
Shifts
Practice 2.0 26 24.0 No turn
Lecture 7.0 56 119.0 No turn

Calendar
Start of activities 26/02/2018 01/06/2018 2020/21 Reg.2014 course timetable

Examination board
Examination board not defined

Syllabus
 Prerequisites: Basic calculus for functions of one real variable. Target skills and knowledge: The course is concerned with the fundamental notions of Probability, whose aim is the modeling of random phenomena. The emphasis is on basic general concept; the aim is to develop the capability of applying these concept to concrete and relevant examples. Examination methods: Written exam. The teacher could require, in special cases, to complete the exam with an oral part. Assessment criteria: The exercises have the aim of verifying the full understanding of basic notion of probability, as well as the capability of applying them to concrete examples. Clarity and coherence of the solutions will also determine the final evaluation. Course unit contents: Random experiments, sample space, probability. Sample space with finitely many elements, combinatorics. Conditional probability and independence. Discrete random variables, discrete density and distribution. Multivariate discrete random variables, joint and marginal densities. Independence of discrete random variables. Expectation for discrete random variables. Variance, covariance, moments. Basic discrete distributions: Binomial, Hypergeometric, Geometric, Negative Binomial, Poisson. Conditional density and conditional expectation for discrete random variables. Absolutely continuous random variables and their expectation. Basin continuous distributions: Uniform, Gamma Normal. Multivariate continuous random variables, joint densities, independence. Conditional density and conditional expectation for absolutely continuous random variables. Law of large numbers and central limit theorem. Normal approximation. Planned learning activities and teaching methods: The presentation of theoretical notions is complemented by examples and exercises. Textbooks (and optional supplementary readings) Sheldon M. Ross, Calcolo delle probabilità. --: Apogeo, 2013. 