- Docente: Fedele Pasquale Greco
- Credits: 10
- SSD: SECS-S/01
- Language: Italian
- Moduli: Aldo Gardini (Modulo 1) Fedele Pasquale Greco (Modulo 2)
- Teaching Mode: Traditional lectures Traditional lectures (Modulo 1) Traditional lectures (Modulo 2)
- Campus: Rimini
- Corso: First cycle degree programme (L) in Statistics, Finance and Insurance (cod. 5901)
-
from Sep 19, 2023 to Oct 23, 2023
-
from Nov 07, 2023 to Dec 12, 2023
Learning outcomes
By the end of the course, the candidate has a solid knowledge of basic statistical inference and has some foundational knowledge about some of the main statistical techniques of data analysis, even when the number of variables is large. In particular, he/she is able to perform many parametric statistical tests, as well as the most used nonparametric tests, is able to get an estimator and to check its properties. He/she is familiar with the fundamental concepts of linear regression model.
Course contents
Part 1
(The following contents refer also to the crash course of STATISTICS of the two year Master, Financial and Actuarial ScincesFinancial and Actuarial Statistics)
- Introduction to statistical inference.
- Sample space, statistics and estimators.
- Finite and asymptotic properties of estimators.
- Methods of estimation.
- Hypothesis testing.
- Statistical tests for mean value, variance and frequency.
- Tests of goodness of fit and independence.
Part 2
Simple linear regression: ordinary least squares estimators and maximum likelihood estimators; the coefficient of determination. Applications with R.
Multiple linear regression: parameter estimation and interpretation; properties of the ordinary least squares estimators; analysis of the resuduals; test of overall regression and subset of the coefficients; model selection.Readings/Bibliography
D. Piccolo, Statistica per le decisoni, Il Mulino, Bologna, 2010, PARTS III and IV.
Teaching methods
Each topic covered in the lectures will be followed by exercises in practical classes using R.
Assessment methods
The final exam aims at evaluating the achievement of the following objectives:
Deep knowledge concerning theoretical topics covered during the lectures;
Ability to analyze real data;
The final test will consist of a computer session and an written test.Teaching tools
Slides and R scripts available on Virtuale.
Office hours
See the website of Fedele Pasquale Greco
See the website of Aldo Gardini