Scheda insegnamento


L'insegnamento contribuisce al perseguimento degli Obiettivi di Sviluppo Sostenibile dell'Agenda 2030 dell'ONU.

Istruzione di qualità

Anno Accademico 2020/2021

Conoscenze e abilità da conseguire

By the end of the course the student acquires the knowledge of descriptive and probabilistic methods for the analysis of contingency tables. The student is also able to choose the best method to perform multivariate analyses of a given categorical dataset and to interpret the obtained results.


Introduction (2 hours)

  • Data matrices and contingency tables
  • Descriptive and inferential techniques for the analysis of contingency tables

Descriptive methods (11 hours)

  • Geometric concepts in multidimensional space
  • Matrix decompositions (spectral, singular value), low-rank matrix approximation and multidimensional analysis
  • Theory and algebra of simple correspondence analysis
  • Canonical correlation analysis of contingency tables
  • Multiple correspondence analysis

Probabilistic methods (11 hours)

  • Probability structure for contingency tables
  • Loglinear models for contingency tables:

- model specification;

  - parameter estimation and interpretation;

- goodness-of-fit measures;

- model selection and comparison;

- diagnostics for checking models.

R functions and packages for the analysis of contingency tables (6 hours)

  • Syntax, usage and output of functions and packages available in the R environment for the analysis of contingency tables
  • Examples of analyses based on the use of such functions and packages

The reported number of hours is an estimate which takes account of both theoretical and practical lessons. Practical lessons will typically take place on Thursday (dates will be announced during the lessons).


Compulsory readings

  • A. Agresti. Categorical data analysis, Second edition. Hoboken: John Wiley & Sons, 2002. Chapters 1-3, 8-9
  • M. Greenacre. Theory and applications of correspondence analysis. London: Academic Press, 1984. Chapters 1-5
  • O. Nenadic, M. Greenacre. Correspondence analysis in R, with two- and three-dimensional graphics: the ca package. Journal of Statistical Software. May 2007, Volume 20, Issue 3
  • Additional readings concerning topics not included in the recommended textbooks (to be announced during the lessons)

Additional materials useful for the preparation of the exam are available on the platform "Virtual learning environment" of the University of Bologna (https://virtuale.unibo.it/) for all enrolled students:

  • slides containing a summary of the course contents as discussed by the teacher during the theoretical lessons;
  • a list of some exercises useful for the preparation of the exam;
  • the materials used by the teacher during the practical lessons;
  • a paper by Redfern (2012) about an analysis of genre preferences in UK film audiences.

In order to have access to the platform "Virtual learning environment", students must use their username and password.

For the preparation of the exam students are supposed to use all the compulsory readings.

Metodi didattici

Theoretical lessons in a lecture hall and practical lessons through the R computing package. R scripts used during the practical lessons will be made available on the platform "Virtual learning environment" of the University of Bologna (https://virtuale.unibo.it/) for all enrolled students. 

Although attending lessons is not mandatory, it is strongly recommended.

Modalità di verifica e valutazione dell'apprendimento

The exam tests the qualifications of each student both on a theoretical and a practical level. It is written, lasts two hours and normally takes place in a room. It may be composed of either closed-ended questions or open-ended questions, some of which concern the theoretical aspects of the statistical methods, while some other are mainly focused on the ability of using methods for data analysis and interpreting results. These latter questions require solving numerical exercises. Consulting textbooks or notes during the written exam is not allowed. A pocket calculator is necessary. The maximum mark for each question is fixed in advance and is visible by the student who takes the exam. The sum of the marks for all questions is 32. The overall final grade is given by the sum of the marks in the exercises, which is expressed on a scale of 30.

Upon request, students who attend the lessons can also take the exam according to an alternative process which is composed of two parts: i) a written exam concerning the probabilistic methods for the analysis of categorical data; ii) a written project report concerning the descriptive methods for the analysis of categorical data. Further information will be provided by the teacher during the first lesson (see also the teaching materials focusing on this process available on the platform "Virtual learning environment").  

Depending on how the coronavirus (COVID-19) pandemic evolves, there would be the need for suitable modifications of these assessment methods. In that case, more notice will be given here.

Further useful information about the exams

  • In order to take the exam, students are required to put their names down for the exam through Almaesami platform.
  • Exams can only be taken in the official exam sessions.
  • An identity card (or the UNIBO student card) is required to take part in the exam.
  • Students will not be permitted to use any electronical device (mobile phones, smart watches, electronical data storage devices, etc.). If you have your mobile phone with you during an exam, you should turn it off and place it under your chair in the exam venue. Students found with a mobile phone on their person are in breach of University regulations and they will not be allowed to finish the exam.
  • Students who wish to withdraw from the exam must do so within the first 30 minutes of the exam. 
  • Students who pass the exam are allowed to retake it no more than twice.

First call - November 6, 2020

  • Each student can take the exam either in person or online.
  • Two separate subscription lists are available on the Almaesami platform. Students are kindly invited to write their name down for the right list. Changes will be possible only when subscription lists are open (from 22/10/2020 to 03/11/2020).
  • In both modes, the exam will be written and will be composed of a set of open-ended questions.
  • In person exam: November 6, 2 PM – 4 PM.
  • Online exam: November 6, 4:15 PM – 6:15 PM.
  • The online exam will take place through the Zoom platform. In order to take the online exam students must use their PC. Information about how to take a written exam online via Zoom is available at the webpage https://www.unibo.it/en/services-and-opportunities/online-services/online-services-for-students-1/lessons-and-exams-online.
  • Before the online exam: students must have installed a free app or software on their smartphone with which they can scan their paper and save it as a single document at the end of their exam (PDF format recommended); they must have been practising the creation of a single file with two or more photos by using the scanning app so as to avoid any technical issues at the end of the exam.
  • During the online exam: students must be by themselves in a well-lit room; they need to have some blank sheets of paper, a pen and, and set up a webcam so that their face and hands and sheets of paper are visible. They must write their name, surname and matriculation number on each sheet of the paper and on each page. Microphones and cameras of all students have to stay on and students must remain silent during the exam. Students' smartphones have to be in sight and face down. If requested by the teacher, the PC webcam should be used to provide a 360-degree view of the room. The teacher will supervise students and will answer any questions via chat. The teacher must be able to access students' cameras at any time during the exam. The teacher may ask to check on a student via the webcam of the Zoom meeting where the student is taking the exam (or via smartphone).
  • At the end of the exam: when the time is up, students must put down their pen and stop writing. At the teacher’s request, they must show each sheet of the paper they have written via webcam. Each student must open the scanning app on their smartphone, take pictures of each sheet of the paper so as to create a single file for their exam, and saved it with the name Surname.pdf. Then, they have to send the so-obtained document (PDF format recommended) to the teacher using their institutional email address (@studio.unibo.it). The teacher will check that all e-mails have been successfully received and will announce the end of the exam.

Strumenti a supporto della didattica

Explanations are generally given by using the slides available on the platform "Virtual learning environment" of the University of Bologna (https://virtuale.unibo.it/) for all enrolled students.

Orario di ricevimento

Consulta il sito web di Gabriele Soffritti