Training and Research

PhD Programme Courses/classes - 2023/2024

Research organisation

Credits: 6

Language: Italian

Teacher:  Ivan Russo, Cecilia Rossignoli, Alessandro Zardini, Ilenia Confente

Qualitative research methods

Credits: 10,5

Language: Italian

Teacher:  Sara Moggi, Lapo Mola, Alice Francesca Sproviero, Alessandro Lai, Riccardo Stacchezzini

Advanced quantitative research methods

Credits: 11

Language: Italian

Teacher:  Elena Claire Ricci, Claudia Bazzani, Alessandro Zardini, Riccardo Scarpa

Trending topics in accounting

Credits: 2

Language: Italian

Teacher:  Stefano Landi

Trending topics in supply chain management

Credits: 2

Language: Italian

Teacher:  Silvia Blasi, Ilenia Confente, David D'Acunto

Classics in Accounting

Credits: 4

Language: English

Teacher:  Francesca Rossignoli, Alessandro Lai, Riccardo Stacchezzini, Cristina Florio

Classics in finance

Credits: 3

Language: Italian

Teacher:  Laura Chiaramonte

Classics in supply chain management

Credits: 4

Language: Italian

Teacher:  Ivan Russo, Barbara Gaudenzi

Content analysis and coding

Credits: 0,8

Language: English

Teacher:  Sara Moggi

Introduction to qualitative methodology, interviews and focus groups

Credits: 0,8

Language: English

Teacher:  Sara Moggi

Trending topics in consumer market research for developing innovation

Credits: 2

Language: Italian

Teacher:  Roberta Capitello, Elena Claire Ricci, Claudia Bazzani

Trending topics in finance

Credits: 2

Language: Italian

Teacher:  Laura Chiaramonte

Trending topics in performance management

Credits: 2

Language: Italian

Teacher:  Silvia Vernizzi, Silvia Cantele

PhD school courses/classes - 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

Credits

1

Language

Italian

Class attendance

Free Choice

Location

VERONA

Learning objectives

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.

Program

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.

Didactic methods

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.

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.