96800 - Statistical Software for Business (Laboratory)

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

The course introduces Python, R and Stata for the management and analysis of economic and business data. Teaching activities will be mainly based on practical lessons carried out in the Positron environment.

The Python module will cover the fundamentals of programming, data management and an introduction to basic predictive procedures. The R module will focus on data transformation, statistical analysis, visualisation and reproducible reporting. The Stata module will address data management and the application of statistical and econometric methods.

Readings/Bibliography

Lynch, S. "Python for Scientific Computing and Artificial Intelligence". ISBN 9781032258713334 Published June 15, 2023 by Chapman & Hall

Wickham H. Advanced r. chapman and hall/CRC; 2019 May 24.

Teaching materials, datasets, scripts and exercises used during the classes will be made available by the instructor.

Teaching methods

Laboratory lectures.

In view of the type of activity and the adopted teaching methods, the attendance at this activity requires the prior participation of all students in Modules 1 and 2 on safety training in the workplace [https://centri.unibo.it/tutela-promozione-salute-sicurezza/it/corsi-di-formazione/formazione-obbligatoria-su-sicurezza-e-salute-per-svolgimento-di-tirocinio-tesi-laboratorio], in e-learning mode.

Assessment methods

Learning outcomes will be assessed through an individual computer-based practical examination. Students will be required to import and organise a dataset, perform selected data transformations, produce descriptive statistics and graphical representations, apply an appropriate statistical method and interpret the resulting output.

Teaching tools

Teaching activities will be carried out in a computer laboratory or using students’ personal computers. The following tools will be used:

• Positron as an integrated environment for writing, executing and organising code;
• Python;
• R;
• Stata;
• datasets, scripts, exercises and supplementary materials provided by the instructor.

Office hours

See the website of Lorenzo Mori