Training and Research
PhD Programme Courses/classes - 2023/2024
This page shows the courses and classes of the PhD programme for the academic year 2023/2024. Additional courses and classes will be added during the year. Please check for updates regularly!
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
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
Free choice teaching activities
Credits: 5
Language: Italian
Mandatory teaching activities (teachers external to the Faculty Board)
Credits: 5
Language: Italian
Teaching activities prof. Flor
Credits: 5
Language: Italian
Teaching activities prof. Nicolini
Credits: 5
Language: Italian
Teaching activities prof. Peruzzi
Credits: 5
Language: Italian
Doctoral seminars
Credits: 5
Language: Italian
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
ENGLISH FOR ACADEMIC PRESENTATION SKILLS [Arts and Humanities]
Credits: 2,5
Language: English
ENGLISH FOR ACADEMIC PRESENTATION SKILLS [Law and Economics]
Credits: 2,5
Language: English
ENGLISH FOR ACADEMIC PRESENTATION SKILLS [Life and Health Sciences - 1 st Session]
Credits: 2,5
Language: English
ENGLISH FOR ACADEMIC PRESENTATION SKILLS [Life and Health Sciences - 2 nd Session]
Credits: 2,5
Language: English
ENGLISH FOR ACADEMIC PRESENTATION SKILLS [Natural Sci. and Engineering-2nd Session]
Credits: 2,5
Language: English
ENGLISH FOR ACADEMIC PRESENTATION SKILLS [Natural Sci. and Engineering-1st Session]
Credits: 2,5
Language: English
Teacher: Monica Antonello
ENGLISH FOR ACADEMIC WRITING SKILLS [Arts and Humanities]
Credits: 2,5
Language: English
ENGLISH FOR ACADEMIC WRITING SKILLS [Law and Economics]
Credits: 2,5
Language: English
ENGLISH FOR ACADEMIC WRITING SKILLS [Life and Health Sciences - 1 st Session]
Credits: 2,5
Language: English
ENGLISH FOR ACADEMIC WRITING SKILLS [Natural Sci. and Engineering-1st Session]
Credits: 2,5
Language: English
Teacher: Monica Antonello
ENGLISH FOR ACADEMIC WRITING SKILLS [Natural Sci. and Engineering-2nd Session]
Credits: 2,5
Language: English
ENGLISH FOR ACADEMIC WRITING SKILLS [Life and Health Sciences - 2 nd Session]
Credits: 2,5
Language: English
Teaching Activities ex DM 226/2021: Research management and Enhancement
SEMINARIO AVANZATO SULLE RISORSE BIBLIOTECARIE PER LA RICERCA [Arts and Humanities]
Credits: 2,5
Language: Italian
Teacher: Donatella Boni
SEMINARIO AVANZATO SULLE RISORSE BIBLIOTECARIE PER LA RICERCA [Law and Economics]
Credits: 2,5
Language: Italian
Teacher: Luisella Zocca
SEMINARIO AVANZATO SULLE RISORSE BIBLIOTECARIE PER LA RICERCA [Scientific Area]
Credits: 2,5
Language: Italian
Teacher: Elena Scanferla
Teaching Activities ex DM 226/2021: Statistics and Computer Sciences
INTRODUCTION TO PROBABILITY (MODULE I)
Credits: 1
Language: English
Teacher: Marco Minozzo
INTRODUCTION TO PROBABILITY (MODULE II)
Credits: 1
Language: English
Teacher: Marco Minozzo
INTRODUCTION TO STATISTICAL INFERENCE
Credits: 1
Language: English
Validità e affidabilità delle misure e dei test diagnostici
Credits: 0,5
Language: English
Teacher: Alessandro Marcon
BASIC LEVEL STATISTICS
Credits: 2,5
Language: English
BASIC LEVEL STATISTICS
Credits: 2,5
Language: Italian
Statistical analysis with R - module I
Credits: 1
Language: Italian
Teacher: Erica Secchettin
GENERALIZED LINEAR MODELS: LOGISTIC REGRESSION, LOGLINEAR MODEL, POISSON MODEL
Credits: 2
Language: English
Teacher: Lucia Cazzoletti
Disegno dello studio nella ricerca osservazionale e sperimentale
Credits: 1,5
Language: English
Teacher: Alessandro Marcon
Calcolo della numerosità campionaria in funzione di una precisione o potenza statistica prefissata
Credits: 1
Language: English
Teacher: Giuseppe Verlato
Introduzione alla meta-analisi per la ricerca biomedica (revisione della letteratura, raccolta dei dati, costruzione del database)
Credits: 1
Language: English
Teacher: Giuseppe Verlato
Applicazioni della meta-analisi in campo epidemiologico e medico
Credits: 1
Language: Inglese
Teacher: Giuseppe Verlato
Survival analysis: log-rank test, Kaplan-Meier survival curves, Cox regression model
Credits: 1,5
Language: Inglese - English
Teacher: Simone Accordini
INTERMEDIATE STATISTICS [Recommended for Human Sciences]
Credits: 2,5
Language: English
INTERMEDIATE STATISTICS [Tutti i corsi di studio]
Credits: 2,5
Language: English
Statistical analysis with R - module II
Credits: 2
Language: Italian
Teacher: Erica Secchettin
Teaching Activities: Free choice
PROTECTING PSYCHOLOGICAL WELL-BEING IN THE PHD PROGRAM: WHAT DO WE NEED TO CONSIDER FOR BEING A GOOD SCIENTIST: BEST PRACTICE AND THE ETHICS OF SCIENCE
Credits: 1
Language: inglese
Teacher: Paola Cesari
QUANDO LA RICERCA SI FA ETICA (PERCORSO ORGANIZZATO E FINANZIATO DAL TEACHING AND LEARNING CENTER DI UNIVR)
Credits: 2
Language: Italian
Teacher: Roberta Silva
LA COMUNICAZIONE UMANISTICA: OPPORTUNITA' E RISCHI
Credits: 1
Language: Italiano
Italian Poetry abroad
Credits: 1
Language: Italiano
Teacher: Massimo Natale
BUSINESS MODEL CANVAS PILL
Credits: 1,5
Language: English
IMPARA IL MARKETING DIGITALE
Credits: 1,5
Language: English
APPROCCI E METODOLOGIE PARTECIPATIVE NELLA RICERCA CON GLI ATTORI DEL TERRITORIO
Credits: 1,5
Language: Italian
Teacher: Cristiana Zara
DOING INTERVIEWS IN QUALITATIVE RESEARCH
Credits: 1,5
Language: English
Teacher: Chiara Sità
DIFFERENTIAL DIAGNOSIS OF DEMYELINATING DISEASES OF THE CENTRAL NERVOUS SYSTEM
Credits: 2
Language: English
Teacher: Alberto Gajofatto
IL SONNO E I SUOI DISTURBI: FOCUS SULLE PARASONNIE E I DISTURBI DEL MOVIMENTO IN SONNO
Credits: 1
Language: English
Teacher: Elena Antelmi
IMAGING TECHNIQUES FOR BODY COMPOSITION ANALYSIS
Credits: 1
Language: English
Teacher: Carlo Zancanaro
OPEN SCIENCE: THE MIGHTY STICK AGAINST "BAD" SCIENCE
Credits: 2
Language: English
Teacher: Alberto Scandola
THE EMPIRICAL PHENOMENOLOGICAL METHOD (EPM): THEORETICAL FOUNDATION AND EMPIRICAL APPLICATION IN EDUCATIONAL AND HEALTHCARE FIELDS
Credits: 2
Language: English
THE PATHWAY OF OXYGEN: CAUSE OF HYPOXEMIA
Credits: 1
Language: English
Teacher: Carlo Capelli
GENERALIZED LINEAR MODELS: LOGISTIC REGRESSION, LOGLINEAR MODEL, POISSON MODEL (2023/2024)
Teacher
Referent
Credits
2
Language
English
Class attendance
Free Choice
Location
VERONA
Learning objectives
An introduction to the fundamentals of generalized regression models will be given in this course, with a focus on models for count, binary, and categorical data. These types of response variables are widely used in industrial applications as well as observational and experimental research.
Upon successful completion of the course, students will be able to:
• Describe the general structure of a GLM and similarities and differences with linear models
• Estimate and interpret a logistic regression model
• Estimate and interpret a Poisson regression model
• Know of issues and some strategies for dealing with overdispersion in some generalised linear models (GLMs)
Prerequisites and basic notions
This course assumes a good understanding of probability and mid-level knowledge of linear regression theory.
Program
The course covers methods for regression analysis of responses that do not follow the normal distribution, especially of discrete responses. We will learn to understand some of the common statistical methods for fitting regression models to such data. In particular, we will consider logistic regression, Poisson regression and log-linear models. The lecture focuses on the development, theoretical justification, and interpretation of these methods.
When and where
Teaching forms mainly consist of lectures (8h) and exercises proposed by the teacher. The teaching material (slides of the theoretical lessons) is made available to the students on the e-learning web page of the course (Moodle platform). Lessons will be delivered via Zoom. Full attendance is required.
Learning assessment procedures
There is no exam
Assessment
There is no exam, hence there is also no definition of the evaluation criteria.
Criteria for the composition of the final grade
There is no grade because there is no exam.
Scheduled Lessons
When | Classroom | Teacher | topics |
---|---|---|---|
Tuesday 19 March 2024 14:30 - 16:30 Duration: 2:00 AM |
https://univr.zoom.us/j/7951194173?pwd=ZVY2QzMzQ253QW9hSVFLY3d2M084dz09 | Lucia Cazzoletti | Introduction to generalised linear models. Review of the general linear model: assumptions of the linear model (independence of observations, homoskedasticity of errors, linearity of coeffiicents) , least squares estimation and maximum likelihood estimation. Main features of the genralised linear model: i) the probability distribution function of the random component of the response variable belongs to the exponential family, ii) a differentiable and monotonic link function relates the mean of the response variable to the linear predictor, a linear combination of coefficients and explanatory variables. |
Tuesday 26 March 2024 14:30 - 16:30 Duration: 2:00 AM |
https://univr.zoom.us/j/7951194173?pwd=ZVY2QzMzQ253QW9hSVFLY3d2M084dz09 | Lucia Cazzoletti | Introduction to the theoretical basis of logistic regression model, commonly used for binary (proportion/percentage) data, as a generalised linear model. Binomial distribution for the outcome binary variable. The link between probability and logodds. Maximum likelihood estimation of the coefficients of the model. Interpretation of the meaning of the regression coefficients and their statistical significance. |
Wednesday 03 April 2024 14:30 - 16:30 Duration: 2:00 AM |
https://univr.zoom.us/j/7951194173?pwd=ZVY2QzMzQ253QW9hSVFLY3d2M084dz09 | Lucia Cazzoletti | Introduction to the theoretical basis of Poisson regression model, commonly used for count data, as a generalised linear model. Poisson distribution for the outcome variable. Maximum likelihood estimation of the coefficients of the model. Interpretation of the meaning of the regression coefficients and their statistical significance. Use of the offset to take into account the different exposure of subjects. Extensions of the Poisson Regression Model: Negative binomial regression model (NBRM), Zero-inflated poisson (ZIP) model, Zero-truncated count data model. |
Wednesday 24 April 2024 14:30 - 16:30 Duration: 2:00 AM |
https://univr.zoom.us/j/7951194173?pwd=ZVY2QzMzQ253QW9hSVFLY3d2M084dz09 | Lucia Cazzoletti | Using Deviances to Compare Models for Logistic and for Poisson Regression Models. Use of the Likelihood Ratio Test to assess the presence of overdispersion. Some hints about the log-linear model in the presence of contingency tables |
Faculty
PhD students
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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 |
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pdf, it, 166 KB, 19/04/24 |
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pdf, en, 193 KB, 19/04/24 |