Training and Research

PhD school courses/classes - 2024/2025

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, instructions will be sent well in advance. 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: if the information you need is not there, then it means that we don't have it yet. As soon as we get new information, we will promptly publish it on this page.

Summary of training activities

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

Teacher

Not yet assigned

Credits

2.5

Language

English

Class attendance

Free Choice

Location

VERONA

Learning objectives

Il corso ha l’obiettivo di permettere di acquisire le competenze necessarie a condurre analisi statistiche più avanzate utili ad interpretare dati di disegni di ricerche complessi, in cui siano presenti più variabili, osservate o latenti. Inoltre saranno date le basi per la interpretazione e la realizzazione di meta-analisi. Tali competenze, a supporto della ricerca, in particolare nell’ambito delle scienze umane, verranno studiate attraverso l’uso di pacchetti statistici opensource (R e JAMOVI).

Program

Programma:

1. ANOVA: Oneway ANOVA, factorial designs, repeated measure designs, mixed designs
2. Path analysis, Mediation and moderation analysis
3. Exploratory and confirmatory factor analysis
4. Introduction to Meta-analysis, focused on Human Sciences Research (literature review, data collection, database construction)
5. Application of meta-analysis in social science and humanities fields
6. Prova di verifica delle competenze acquisite

Didactic methods

il corso di Statistica – Livello Intermedio sarà organizzato su due sessioni distribuite nel corso dell’a.a.

- Sessione 1: docenti interni UNIVR (Professoresse Brondino, Menardo), max 30 persone. Il corso sarà a distanza, sulla piattaforma Zoom, con frequenza obbligatoria ad almeno il 70% delle ore. Prova di verifica al termine della sessione.
- Sessione 2: docenti esterni da selezionare tramite bando, max 30 persone. Il corso sarà a distanza, sulla piattaforma Zoom, con frequenza obbligatoria ad almeno il 70% delle ore. Prova di verifica al termine della sessione.

PhD students

PhD students present in the:
Course lessons
PhD Schools lessons

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Guidelines for PhD students

Below you will find the files that contain the Guidelines for PhD students and rules for the acquisition of ECTS credits (in Italian: "CFU") for the Academic Year 2023/2024.

Documents

Title Info File
File pdf Guidelines for PhD students pdf, en, 146 KB, 02/04/24
File pdf Linee guida del percorso formativo pdf, it, 210 KB, 02/04/24