First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Science
MATHEMATICS
Course unit
MATHEMATICAL STATISTICS
SC01107882, A.A. 2019/20

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

Information on the course unit
Degree course First cycle degree in
MATHEMATICS
SC1159, Degree course structure A.Y. 2008/09, A.Y. 2019/20
N0
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Number of ECTS credits allocated 6.0
Type of assessment Mark
Course unit English denomination MATHEMATICAL STATISTICS
Website of the academic structure http://matematica.scienze.unipd.it/2019/laurea
Department of reference Department of Mathematics
Mandatory attendance No
Language of instruction Italian
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 MARCO FORMENTIN MAT/06
Other lecturers FRANCESCA COLLET MAT/06

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Core courses MAT/06 Probability and Mathematical Statistics 6.0

Course unit organization
Period First semester
Year 3rd Year
Teaching method frontal

Type of hours Credits Teaching
hours
Hours of
Individual study
Shifts
Practice 3.0 24 51.0 No turn
Lecture 3.0 24 51.0 No turn

Calendar
Start of activities 30/09/2019
End of activities 18/01/2020
Show course schedule 2019/20 Reg.2008 course timetable

Examination board
Board From To Members of the board
8 Statistica Matematica - a.a. 2019/2020 01/10/2019 30/09/2020 FORMENTIN MARCO (Presidente)
COLLET FRANCESCA (Membro Effettivo)
BARBATO DAVID (Supplente)
BIANCHI ALESSANDRA (Supplente)
CALLEGARO GIORGIA (Supplente)
FISCHER MARKUS (Supplente)

Syllabus
Prerequisites: Prerequisites: Basic probability and Statistics. Fundamental notions of analysis and linear algebra.
Target skills and knowledge: It is expected that, at the end of the course, students are familiar with certain fields of classical statistics such as parametric estimation and hypothesis testing. In particular, they must learn some fundamental distributions such as those of exponential class. They must also be capable of applying tools and concepts of analysis and linear algebra to study such problems.
Examination methods: Written test.
Assessment criteria: Evaluation will be based on the following criteria:
1. Comprehension of the covered fundamental concepts;
2. Capability of calculating closed form solutions in simple problems;
3. Thoroughness of preparation;
4. Clarity of exposition.
Course unit contents: This is an introductory course to the basic concepts of classical statistics from a predominantly mathematical point of view. Course program:
- Introductory notions on problems and methods of mathematical statistics;
- Statistics, sufficient statistics; exponential class distributions;
- Unbiased estimators with uniformly minimum variance;
- Rao-Cramer lower bound and efficient estimators;
- Linear models. Least squares principle;
- Maximum likelihood estimators;
- Test for simple alternative hypotheses; Neyman-Pearson test.
- Introduction to Statistics of Stochastic Processes
Planned learning activities and teaching methods: Frontal lectures. The theoretical part is continuously illustrated through examples. Moreover, exercises to be worked out at home are proposed for each topic.
Textbooks (and optional supplementary readings)
  • G.Andreatta e W.Runggaldier, Statistica Matematica: Problemi ed Esercizi Risolti. --: Liguori Editore, 1983. Cerca nel catalogo
  • M. Pavon, Appunti di statistica matematica.. --: Disponibili nel sito del corso, 2014.
  • Hogg, Robert V.; Craig, Allen T., Introduction to mathematical statistics. New York: Macmillan, London, Collier Macmillan, 1978. Cerca nel catalogo