Formazione e ricerca

Attività Formative della Scuola di Dottorato - 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

THE EMPIRICAL PHENOMENOLOGICAL METHOD (EPM): THEORETICAL FOUNDATION AND EMPIRICAL APPLICATION IN EDUCATIONAL AND HEALTHCARE FIELDS

Crediti: 2

Lingua di erogazione: English

Docente:  Luigina Mortari

DOTTORATO E MERCATO DEL LAVORO: WORKSHOP FORMATIVI PER DOTTORANDI E NEO-DOTTORI DI RICERCA

Crediti: 4

Lingua di erogazione: Italiano

ARE YOU SURE YOU CAN DEFEAT A CHATBOT?

Crediti: 1

Lingua di erogazione: Italiano

MEETING UKRAINE: THE IMPACT OF WAR AND FUTURE OPPORTUNITIES

Crediti: 1

Lingua di erogazione: Italiano

EMOTIONS, BELIEFS, AND SKILLS TO FACE CLIMATE CHANGE AND EMBRACE CLIMATE ACTION

Crediti: 0,5

Lingua di erogazione: Inglese

OPEN SCIENCE: THE MIGHTY STICK AGAINST "BAD" SCIENCE

Crediti: 2

Lingua di erogazione: English

Docente:  Michele Scandola

COMPUTATIONAL MECHANISMS UNDERLYING SENSORIMOTOR LEARNING

Crediti: 4,5

Lingua di erogazione: English

Docente:  Matteo Bertucco

CSF DYNAMICS: ANATOMICAL AND FUNCTIONAL FEATURES

Crediti: 0,5

Lingua di erogazione: Inglese

Docente:  Alberto Feletti

DIFFERENTIAL DIAGNOSIS OF DEMYELINATING DISEASES OF THE CENTRAL NERVOUS SYSTEM

Crediti: 2

Lingua di erogazione: English

Docente:  Alberto Gajofatto

IL SONNO E I SUOI DISTURBI: FOCUS SULLE PARASONNIE E I DISTURBI DEL MOVIMENTO IN SONNO

Crediti: 1,5

Lingua di erogazione: italiano o inglese

Docente:  Elena Antelmi

IMAGING TECHNIQUES FOR BODY COMPOSITION ANALYSIS

Crediti: 1

Lingua di erogazione: Inglese/English

Docente:  Carlo Zancanaro

RESEARCH TECHNIQUES IN NEUROSCIENCE: MONITORING AND MODULATING NEURONAL ACTIVITY

Crediti: 2,3

Lingua di erogazione: non prevista

Docente:  Giuseppe Busetto

Crediti

1

Lingua di erogazione

English

Frequenza alle lezioni

Scelta Libera

Sede

VERONA

Obiettivi di apprendimento

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.

Prerequisiti e nozioni di base

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.

Programma

- 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.

Bibliografia

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.

Modalità didattiche

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.

Modalità di verifica dell'apprendimento

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

Le/gli studentesse/studenti con disabilità o disturbi specifici di apprendimento (DSA), che intendano richiedere l'adattamento della prova d'esame, devono seguire le indicazioni riportate QUI

Dottorandi

Dottorandi presenti nel:
Lezioni del Corso
Lezioni della Scuola di Dottorato

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Linee guida percorso formativo

Di seguito i file che contengono le Linee guida per il percorso formativo e il regolamento per l'acquisizione dei crediti formativi (CFU) per l'Anno Accademico 2023/2024.

Documenti

Titolo 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