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 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

PhD students

PhD students present in the:

No people are present.

Course lessons
PhD Schools lessons

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