- Docente: Cinzia Franceschini
- 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)
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dal 18/09/2023 al 24/10/2023
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
Learning outcomes
By the end of the course, the student will be able to use the R software to deal with business data structures, using both univariate and multivariate statistical approaches. The student will be able to deal with the practical applications of several statistical methods.
Course contents
Introduction to R:
What is R? Downloading and installing.
R basic commands and data structures.
Data import and cleaning.
Functions.
Descriptive statistics and Basic graphs.
Business data analysis with R: application of some statistical methods through R (univariate statistics, bivariate statistics, linear regression).
Testi/Bibliografia
Peter Dalgaard. Introductory Statistics with R. Springer, New York, 2002.
John Verzani. Using R for Intoductory Statistics. Chapman & Hall/CRC, Boca Raton, FL, 2005.
Slides of the course.
Metodi didattici
Slides and computer laboratory sessions
Modalità di verifica e valutazione dell'apprendimento
One hour written test with TRUE/FALSE questions and practical R exercises
The evaluation will be expressed in grades 0-30
Strumenti a supporto della didattica
Slides, datasets, scripts
Orario di ricevimento
Consulta il sito web di Cinzia Franceschini