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

Academic staff

Margherita Brondino, Elisa Menardo , Elisa Menardo

Credits

2.5

Language

English

Class attendance

Free Choice

Learning objectives

The course aims to provide the expertise that is required to perform base-level statistical analysis, both descriptive and inferential, for research purposes. The course mainly targets human sciences, also with the aid of open source statistical software (JAMOVI).

Program

1. Introduction to empirical research (measurement issues, research designs, data collection) (4 hours)
2. Introduction to statistics: Descriptive statistics and graphical representation (4 hours)
3. Null hypothesis testing, t-test, Chi-square (4 hours)
4. Correlational analysis, Simple and multiple linear regression analysis, and hierarchical regression (4 hours)
5. Exercises on all course contents (2 hours)
6. Test on acquired expertise (2 hours)

When and where

The course will be delivered via Zoom; at least 70% attendance is required.
At most 20 students will be admitted; precedence will be given to students in the Arts and Humanities area.
Calendar
4 October 2022, 9.00-13.00, Lesson 1
18 October 2022, 9.00-13.00, Lesson 2
8 November 2022, 9.00-13.00, Lesson 3
22 November 2022, 9.00-13.00, Lesson 4
29 November 2022, 9.00-11.00, Lesson 5
6 December 2022, 9.00-11.00, final test
Zoom link for all lessons https://univr.zoom.us/j/83091709903?pwd=Ymovc3RjeFlianlPMDlpdGFDYmM5dz09

Scheduled Lessons

When Classroom Teacher topics
Thursday 01 February 2024
08:00 - 10:00
Duration: 2:00 AM
To be defined Margherita Brondino Introduction to empirical research (measurement issues, research designs)
Thursday 08 February 2024
08:00 - 10:00
Duration: 2:00 AM
To be defined Margherita Brondino Introduction to empirical research (measurement issues, research designs, data collection)
Thursday 07 March 2024
09:00 - 13:00
Duration: 4:00 AM
To be defined Margherita Brondino
Elisa Menardo
BASIC LEVEL STATISTICS - RECOMMENDED FOR HUMAN SCIENCES
BASIC LEVEL STATISTICS - RECOMMENDED FOR HUMAN SCIENCES
Tuesday 12 March 2024
09:00 - 13:00
Duration: 4:00 AM
To be defined Margherita Brondino
Elisa Menardo
BASIC LEVEL STATISTICS - RECOMMENDED FOR HUMAN SCIENCES
BASIC LEVEL STATISTICS - RECOMMENDED FOR HUMAN SCIENCES
Thursday 14 March 2024
09:00 - 13:00
Duration: 4:00 AM
To be defined Margherita Brondino
Elisa Menardo
BASIC LEVEL STATISTICS - RECOMMENDED FOR HUMAN SCIENCES
BASIC LEVEL STATISTICS - RECOMMENDED FOR HUMAN SCIENCES
Tuesday 19 March 2024
09:00 - 13:00
Duration: 4:00 AM
To be defined Margherita Brondino
Elisa Menardo
BASIC LEVEL STATISTICS - RECOMMENDED FOR HUMAN SCIENCES
BASIC LEVEL STATISTICS - RECOMMENDED FOR HUMAN SCIENCES
Tuesday 26 March 2024
10:00 - 11:00
Duration: 1:00 AM
To be defined Margherita Brondino
Elisa Menardo
BASIC LEVEL STATISTICS - RECOMMENDED FOR HUMAN SCIENCES
BASIC LEVEL STATISTICS - RECOMMENDED FOR HUMAN SCIENCES

Faculty

PhD students

PhD students present in the:

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Course lessons
PhD Schools lessons

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