Training and Research

PhD school courses/classes - 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

Credits

1

Language

English

Class attendance

Free Choice

Location

VERONA

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.

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

- 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.

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.

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
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 (2024/2025) pdf, it, 104 KB, 29/10/24
File pdf PhD students: general guidelines (2024/2025) pdf, en, 107 KB, 29/10/24