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

English

Class attendance

Free Choice

Learning objectives

The purpose of the modules is to explain, at an intermediate level, the basis of probability theory and some of its more relevant theoretical features.
The topics will be illustrated and explained through many examples.
Students are expected to acquire the language and the concepts needed to better understand the probabilistic models and the statistical techniques used in their subjects.

Prerequisites and basic notions

There are no particular learning requirements. Students should have already been introduced (though at an elementary level) to probability and statistics. Students should also have some confidence in elementary set theory and mathematical calculus.

Program

- Random experiments, events, event trees.
- Algebras and sigma-algebras, axiomatic definition of probability, probability spaces, properties of probability.
- Conditional probability, Bayes theorem, stochastic independence for events.
- Random variables, measurability, cumulative distribution function.

Bibliography

Visualizza la bibliografia con Leganto, strumento che il Sistema Bibliotecario mette a disposizione per recuperare i testi in programma d'esame in modo semplice e innovativo.

Didactic methods

Lessons will be delivered via Zoom; recordings will be made available by the lecturer. Attendance is not required, but passing a written test is required to obtain credits.
WHEN/WHERE
4 October 2023, 14:00-17:00
6 October 2023, 9:00-12:00
18 October 2023, 14:00-16:00

Learning assessment procedures

The final assessment will be through a written paper. Alternatively there will be a Moodle QUIZ.

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE

Scheduled Lessons

When Classroom Teacher topics
Wednesday 04 October 2023
14:00 - 17:00
Duration: 3:00 AM
https://moodledidattica.univr.it/course/view.php?id=15631 Marco Minozzo Introduction to probability (module I)
Friday 06 October 2023
09:00 - 12:00
Duration: 3:00 AM
https://moodledidattica.univr.it/course/view.php?id=15631 Marco Minozzo Introduction to probability (module I)
Wednesday 18 October 2023
14:00 - 16:00
Duration: 2:00 AM
https://moodledidattica.univr.it/course/view.php?id=15631 Marco Minozzo Introduction to probability (module I)

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.