- Docente: Marco Berrettini
- Credits: 6
- Language: English
- Teaching Mode: Traditional lectures
- Campus: Bologna
- Corso: Second cycle degree programme (LM) in Statistics, Economics and Business (cod. 8876)
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from Sep 19, 2022 to Oct 25, 2022
Learning outcomes
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.
Course contents
R
- Session management
- Language essentials
- Data entry and handling
- Descriptive statistics and graphics
- Statistical inference
- Programming
SAS
- The interface
- Importing data
- Modifying data
- Summarizing data
- Basic statistical procedures
Python
- Overview
Readings/Bibliography
Suggested readings:
- 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.
Teaching methods
Computer laboratory sessions, group work.
In consideration of the type of activity and teaching methods adopted, attending this course requires students to have preemptively undergone Modules 1 and 2 about security when in rooms and laboratories for studying, through the e-learning platform (https://elearning-sicurezza.unibo.it/).
Assessment methods
The final exam aims at evaluating the acquired capability to exploit statistical softwares for elaborating statistical reports on business data.
Students will be asked to choose among a list of datasets to analyze using both R and SAS. Small groups can be arranged to work on the report throughout the course. The deliverable will be discussed during the oral exam.
The evaluation will be expressed as eligibility (binary outcome).
Teaching tools
- Scripts
- Datasets
- Slides
Office hours
See the website of Marco Berrettini