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Introduction to Quantitative Methods (SPS-MEMWP-QM-23)

SPS-MEMWP-QM-23


Department SPS
Course category SPS Methods Seminar
Course type Seminar
Academic year 2023-2024
Term 1ST TERM
Credits 20 (EUI SPS Department)
Professors
Contact Fanti, Claudia
  Course materials
Sessions

02/10/2023 11:00-13:00 @ Seminar Room, Villa Malafrasca

03/10/2023 11:00-13:00 @ Seminar Room, Villa Malafrasca

09/10/2023 11:00-13:00 @ Seminar Room 4, Badia Fiesolana

10/10/2023 11:00-13:00 @ Seminar Room 4, Badia Fiesolana

16/10/2023 11:00-13:00 @ Seminar Room 3, Badia Fiesolana

17/10/2023 11:00-13:00 @ Seminar Room 3, Badia Fiesolana

23/10/2023 11:00-13:00 @ Sala del Capitolo, Badia Fiesolana

24/10/2023 11:00-13:00 @ Sala del Capitolo, Badia Fiesolana

30/10/2023 11:00-13:00 @ Sala del Capitolo, Badia Fiesolana

31/10/2023 11:00-13:00 @ Sala del Capitolo, Badia Fiesolana

06/11/2023 11:00-13:00 @ Sala del Capitolo, Badia Fiesolana

07/11/2023 11:00-13:00 @ Seminar Room 3, Badia Fiesolana

13/11/2023 11:00-13:00 @ Sala del Capitolo, Badia Fiesolana

14/11/2023 11:00-13:00 @ Seminar Room 3, Badia Fiesolana

20/11/2023 11:00-13:00 @ Sala del Capitolo, Badia Fiesolana

21/11/2023 11:00-13:00 @ Seminar Room 3, Badia Fiesolana

27/11/2023 11:00-13:00 @ Sala del Capitolo, Badia Fiesolana

28/11/2023 11:00-13:00 @ Seminar Room 4, Badia Fiesolana

05/12/2023 11:00-13:00 @ Seminar Room 3, Badia Fiesolana

Purpose

This comprehensive course serves as an introduction to the essential quantitative methods utilized in the social sciences. Its primary objective is to equip students with the foundational skills necessary for conducting research. Throughout the course, students will gain proficiency in descriptive and inferential statistics, develop an understanding of causality issues, and learn basic statistical programming using R. The course curriculum also encompasses the exploration of databases and guides students in locating suitable data sources for their analytical needs. Additionally, it introduces them to alternative data types, such as text-as-data analysis. Emphasizing practical application, the course employs a variety of examples to illustrate theoretical principles underlying different techniques and methods. While mathematical aspects are essential, this course ensures they are kept to a minimum, allowing students from diverse academic backgrounds to comfortably engage with the material. Consequently, no prerequisites are expected for enrollment. Register for this course

Page last updated on 05 September 2023