37321 - Statistics for Data Analysis

Academic Year 2023/2024

  • Teaching Mode: Traditional lectures
  • Campus: Bologna
  • Corso: Second cycle degree programme (LM) in Economics, Consultancy and Accounting (cod. 5981)

Learning outcomes

At the end of the course the student will have acquired knowledge of the main tools used in auditing for statistical sampling and basic concepts of prediction and classification. The student will be able to study the dependence of a selected variable from a set of explanatory variables through a multiple regression model; to tackle problems of classification both through discriminant analysis and logistic regression.

Course contents

Introduction to R and RStudio.

Data structures in R. Creation and management of variables and dataframes. Data importing.

Descriptive analysis of data and graphical representations.

Statistical inference for the mean of a gaussian population and for a proportion. Comparison of means and proportion of two population.

Simple and multiple linear regression model. Residual analysis.


The following books are freely available on the internet.

Wickham, Hadley, and Grolemund, Garrett. R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. Stati Uniti, O'Reilly Media, 2016. https://r4ds.had.co.nz

Måns Thulin, Modern statistics with R, 2021. http://modernstatisticswithr.com/

The following book is available in bookshops:

Alan Agresti, Maria Kateri, Foundations of Statistics for Data Scientists with R and Python, Taylor & Francis, 2021


Teaching methods

Class lectures.

Each student will need to bring his/her own laptop.

Assessment methods

The exam will be written and will be a practical test of data analysis in a computer laboratory.

Teaching tools

Material provided by the lecturer on virtuale.unibo.it https://virtuale.unibo.it

Statistical software R https://www.r-project.org

Integrated development environment RStudio https://www.rstudio.com

Students with disability or specific learning disabilities (DSA) are required to make their condition known to find the best possibile accomodation to their needs.

Office hours

See the website of Federica Galli


Quality education

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