Formazione e ricerca

Attività Formative del Corso di Dottorato - 2023/2024

L'offerta formativa viene gestita ed erogata dall'Univeristà di Trento

Offerta formativa da definire

Attività Formative della Scuola di Dottorato - 2023/2024

Please note: Additional information will be added during the year. Currently missing information is labelled as “TBD” (i.e. To Be Determined).

PhD students must obtain a specified number of CFUs each year by attending teaching activities offered by the PhD School.
First and second year students must obtain 8 CFUs. Teaching activities ex DM 226/2021 provide 5 CFUs; free choice activities provide 3 CFUs.
Third year students must obtain 4 CFUs. Teaching activities ex DM 226/2021 provide 2 CFUs; free choice activities provide 2 CFUs.

Registering for the courses is not required unless explicitly indicated; please consult the course information to verify whether registration is required or not. When registration is actually required, no confirmation e-mail will be sent after signing up.

Teaching Activities ex DM 226/2021: Linguistic Activities

Teaching Activities ex DM 226/2021: Research management and Enhancement

Teaching Activities ex DM 226/2021: Statistics and Computer Sciences

Teaching Activities: Free choice



Lingua di erogazione


Frequenza alle lezioni

Scelta Libera



Obiettivi di apprendimento

The course aims at introducing the participants to R and to some of its most powerful innovations, which have recently reshaped the way the R code is designed. The approach of the course is mainly applicative, and particular attention is devoted to some topics which are becoming more and more relevant in research, and typically entails highly time-consuming activities, such as data manipulation and code documentation. A unified conceptual framework is provided on model fitting, in order to make participants able to cope with different (and new) regression models autonomously and efficiently.This module
introduces the participants to R language and to its basic functions for statistical analysis of data and stochastic simulations.


1. Introduction to R: R and RStudio; working directory and workspace; special values; types and R objects: scalars, vectors, matrices, data.frame, lists; indexes; matrix operations; definition of new functions; the function str and the help of R.
2. Basic statistics with R: factor variables and the cut function; basic statistical functions; frequency tables and basic statistical tests; probability distributions; (pseudo)-random number generators and seeds; introduction to Monte Carlo simulations.

Quando e Dove

13 March 2024, 12:00-15:00
Aula E, Istituti Biologici
26 March 2024, 12:00-15:00
Aula 4, Lente Didattica
3 April 2024, 12:00-14:00
Aula E, Istituti Biologici

Lessons will be delivered in presence. At least 75% attendance is required.



Dottorandi presenti nel:

Non è presente alcuna persona. 40° Ciclo non iniziato.

Lezioni del Corso
Lezioni della Scuola di Dottorato