Training and Research

PhD Programme Courses/classes - 2023/2024

L'offerta formativa viene gestita ed erogata dall'Univeristà di Trento

Training offer to be defined

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 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

- Discrete random variables, binomial distribution.
- Continuous random variables, density functions.
- Transformations of random variables.
- Expectation, variance and moments of random variables.
- Multidimensional random variables, discrete multidimensional random variables, marginal and conditional distributions, independent random variables.
- Linear combinations of random variables.
- Introduction to limit theorems, weak law of large numbers.

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.

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.
27 October 2023, 14:00-17:00
10 November 2023, 14:00-17:00
24 November 2023, 14:00-16:00
Moodle link

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
Friday 27 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 II)
Friday 10 November 2023
14:00 - 17:00
Duration: 3:00 AM
https://moodledidattica.univr.it/course/view.php?id=15631 Marco Minozzo Introduction to probability (module II)
Friday 24 November 2023
14:00 - 16:00
Duration: 2:00 AM
https://moodledidattica.univr.it/course/view.php?id=15631 Marco Minozzo Introduction to probability (module II)

Faculty

PhD students

PhD students present in the:

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Course lessons
PhD Schools lessons

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