Formazione e ricerca

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).

1. 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.
More information regarding CFUs is found in the Handbook for PhD Students: https://www.univr.it/phd-vademecum

2. 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. Please do not enquiry: if you entered the requested information, then registration was silently successful.

3. When Zoom links are not explicitly indicated, courses are delivered in presence only.

4. All information we have is published here. Please do not enquiry for missing information or Zoom links: as soon as we get new information, we will promptly publish it on this page.

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

Statistical analysis with R - module II  (2023/2024)

Docente

Erica Secchettin

Referente

Erica Secchettin

Crediti

2

Lingua di erogazione

Italiano

Frequenza alle lezioni

Scelta Libera

Sede

VERONA

Seminari 0

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 participant to advanced tools such as graphics, data manipulation and regression analysis with R.

Modalità didattiche

3 April, 14:00-15:00
10 April 2024, 12:00-15:00
23 April 2024, 9:00-11:00
7 May 2024, 9:00-11:00
Aula F, Istituti Biologici

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