Training and Research

PhD Programme Courses/classes - 2023/2024

Business and Company Law

Credits: 0,5

Language: Italian

Teacher:  Giuliana Scognamiglio, Lorenzo Benedetti, Mar Bustillo, Gianluca Guerrieri, Monica Attanasio, Silvia Scalzini, Laura Zoboli, Bernardo Calabrese, Federica Pasquariello, Paola Manes

Seminari Scienze Giuridiche

Credits: 14,5

Language: Italian

An Introduction to Legal Geography

Credits: 1

Language: Italian

Teacher:  R. Houghton, Matteo Nicolini, Jaakko Husa, MIchele Graziadei, Tommaso Amico di Meane

Il caso Cilevics: tra identità nazionale e tutela delle minoranze linguistiche

Credits: 0,5

Language: Italian

Teacher:  Prof. Giacomo Di Federico, Caterina Fratea

Women’s Property Rights under Cedaw

Credits: 0,5

Language: Italian

Teacher:  Prof. José Alvarez

Comparative Private Law

Credits: 1

Language: Italian

Teacher:  Andrea Fusaro, Marco Torsello, Giuditta Cordero-Moss

Crypto-activities in the MiCAr between case and discipline

Credits: 0,5

Language: Italian

Teacher:  Michele De Mari

Cybercrime e Cybersecurity

Credits: 1

Language: Italian

Teacher:  Roberto Flor

Diritto Tributario

Credits: 1

Language: Italian

Teacher:  Maria Grazia Ortoleva, M.P. Alguacil, A. Guidara, L. Del Federico, C. Verrigni

Economic Law

Credits: 1

Language: Italian

Teacher:  Matteo Ortino, Giuseppe Mazziotti, Federico Ferretti

Protezione dei dati personali e rapporto di lavoro subordinato

Credits: 1

Language: Italian

Teacher:  Marco Peruzzi

The Third Legal Family: Mixed Jurisdiction Law in the State of Louisiana

Credits: 0,5

Language: Italian

Teacher:  Stefano Troiano

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).

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

Credits

1

Language

English

Class attendance

Free Choice

Learning objectives

The purpose of the module is to explain, at an elementary level, the conceptual basis of the classical (frequentist) approach to statistical inference. 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 inferential procedures required for their subjects.

Program

- Revision of limit theorems: weak law of large numbers; central limit theorem.
- Random samples, sample statistics and sampling distributions; normal and Bernoulli populations; sample mean, sample variance and sample proportion.
- Point estimation: estimators, unbiasedness, efficiency, mean square error, consistency.
- Interval estimation: pivotal quantity; paradigmatic examples.
- Hypothesis testing: type I and type II errors; critical value; confidence level; power; test statistic; observed significance level, paradigmatic examples.

When and where

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.
26 February 2024, 14:00-17:00
27 February 2024, 14:00-17:00
28 February 2024, 14:00-16:00
Moodle link

Scheduled Lessons

When Classroom Teacher topics
Monday 26 February 2024
14:00 - 17:00
Duration: 3:00 AM
To be defined Marco Minozzo INTRODUCTION TO STATISTICAL INFERENCE
Tuesday 27 February 2024
14:00 - 17:00
Duration: 3:00 AM
To be defined Marco Minozzo INTRODUCTION TO STATISTICAL INFERENCE
Wednesday 28 February 2024
14:00 - 16:00
Duration: 2:00 AM
To be defined Marco Minozzo INTRODUCTION TO STATISTICAL INFERENCE

Faculty

A B C D F G L M N O P R S T V

Bercelli Jacopo

symbol email jacopo.bercelli@univr.it symbol phone-number +39 045 8425320

Calafà Laura

symbol email laura.calafa@univr.it symbol phone-number +39 045 8425337

De Mari Michele

symbol email michele.demari@univr.it symbol phone-number 045 802 8226

Flor Roberto

symbol email roberto.flor@univr.it

Fratea Caterina

symbol email caterina.fratea@univr.it symbol phone-number 045 842 5358

Guiglia Giovanni

symbol email giovanni.guiglia@univr.it symbol phone-number 045 802 8225

Ligugnana Giovanna

symbol email giovanna.ligugnana@univr.it symbol phone-number +39 045 8425392

Meruzzi Giovanni

symbol email giovanni.meruzzi@univr.it symbol phone-number +39 045 8425315

Nicolini Matteo

symbol email matteo.nicolini@univr.it symbol phone-number +39 045 8425393

Omodei Sale' Riccardo

symbol email riccardo.omodeisale@univr.it symbol phone-number 045 8425355

Ortino Matteo

symbol email matteo.ortino@univr.it symbol phone-number +39 045 8425330

Ortoleva Maria Grazia

symbol email mariagrazia.ortoleva@univr.it symbol phone-number 045 802 8052

Palermo Francesco

symbol email francesco.palermo@univr.it symbol phone-number +39 045 8425378

Pasquariello Federica

symbol email federica.pasquariello@univr.it symbol phone-number 045 802 8233

Pedrazza Gorlero Cecilia

symbol email cecilia.pedrazzagorlero@univr.it symbol phone-number +39 045 8425350

Pelloso Carlo

symbol email carlo.pelloso@univr.it symbol phone-number +390458425326

Peruzzi Marco

symbol email marco.peruzzi@univr.it symbol phone-number 045 8425338

Ragno Francesca

symbol email francesca.ragno@univr.it symbol phone-number +39 045 8425398

Rossi Giovanni

symbol email giovanni.rossi@univr.it symbol phone-number +39 045 8425340

Torsello Marco

symbol email marco.torsello@univr.it symbol phone-number +39 045 8425381

Troiano Stefano

symbol email stefano.troiano@univr.it symbol phone-number +39 045 8425317

PhD students

PhD students present in the:

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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 Dottorandi: Linee guida generali pdf, it, 166 KB, 19/04/24
File pdf PhD students: General guidelines pdf, en, 193 KB, 19/04/24