- Docente: Marco Berrettini
- Crediti formativi: 6
- Lingua di insegnamento: Inglese
- Modalità didattica: Convenzionale - Lezioni in presenza
- Campus: Bologna
- Corso: Laurea Magistrale in Statistica, economia e impresa (cod. 8876)
Conoscenze e abilità da conseguire
At the end of the course the student is able to use different statistical software useful to explore and analyse commonly used business data structures, as well as to manipulate and integrate data from different sources. Moreover, the student knows the modern tools for graphical representation currently used for Business Data Visualization. In particular the student is able: - to use SAS and R programming and tools to clean, arrange, select and manipulate business data, and the basics of using logical operators to pre-process data; - to use SAS and R programming and tools explore business data; - to program using Python language to manage applications, management systems and digital systems transversal to many industries and companies.
Contenuti
R
- Downloading and installing
- Session management
- Language essentials
- Data entry
- Descriptive statistics and graphics
- Hypothesis testing
- (Generalized) linear models
- Programming
SAS
- Introduction, the interface
- Importing data
- Creating reports
- Summarizing and graphing data
- Basic statistical procedures
Python
- Overview
Testi/Bibliografia
- P. Dalgaard (2008). Introductory statistics with R (Second Edition). New York: Springer.
- Delwiche, L.D., & Slaughter, S.J. (2012). The Little SAS Book: A Primer (Fifth Edition). SAS Institute.
Metodi didattici
Computer laboratory sessions.
Modalità di verifica e valutazione dell'apprendimento
The final exam aims at evaluating the acquired capability to exploit statistical softwares for elaborating a report.
By the exam day, students will be asked to choose among a list of projects, each consisting in the analysis of a specific data set, which will have to be carried out on R and/or SAS. The results of the study will be presented during the exam, focusing also on the functions/procedures used. Some related questions can be asked during or after the presentation.
Evaluation will be expressed in terms of elegibility (binary outcome: passed or not).
Strumenti a supporto della didattica
- Slides
- Datasets
- Scripts
Orario di ricevimento
Consulta il sito web di Marco Berrettini