- Docente: Elena Loli Piccolomini
- Credits: 6
- SSD: MAT/08
- Language: Italian
- Teaching Mode: Traditional lectures
- Campus: Bologna
- Corso: First cycle degree programme (L) in Information Science for Management (cod. 8014)
Learning outcomes
At the end of the course the student has acquired: -the knowledge of software tools for the data analysis - the definition and the main characteristics of continuous and discrete distributions with their moments -The Maximum Likelihood method for parameters estimation - some numerical methods for linear regression and its application in economy - the main concepts of Statistical Learning for regression and classification
Course contents
Definitions and examples on probability. Discrete and
continuous distributions. Descriptive statistics. Points and
interval estimations. Hypothesis test. Least squares data
approximation: linear regression, polynomial functions of higher
order and nonlinear least squares. Numerical methods for the solution of the discrete linear
least squares problem.
Simulations and programming environment R. Principal functions for
graphics and data analysis. Guided exercises on examples with
simulated and real data.
Introduction to statistical learning. Classification task.
Readings/Bibliography
1) E. Loli
Piccolomini, A. Messina, Statistica e calcolo con R, McGraw-Hill
Education, settembre 2015
2)J. K. Kerns, Introduction to probability and statistics using R,
download from CRAN
3) Casella, Fienberg, Olkin, An introduction to Statistical learning with a applications in R, Springer.
Teaching methods
Lessons and guided exercises on laptop.The exercises consist in small programs in the R
In relation to the kind of activities and didactical methods adopted, the attendance to this class will require the preliminary participation of all the students to the Modules 1 and 2 of the Safety rules on study places, which can ne followed remotely in e-learning via the following link: [https://elearning-sicurezza.unibo.it/environment on the main topics dealed with in the lessons.
Assessment methods
The student must deliver a project assigned during the lessons. the exam is written.
Teaching tools
Example program files given by the teacher.
Office hours
See the website of Elena Loli Piccolomini
SDGs


This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.