Advanced Quantitative Methods

Dozent/in	Prof. Dr. Stefan Boes; Noel Ackermann, MA; Dr. sc. Tess Bardy
Veranstaltungsart	Vorlesung/Übung
Code	FS241011
Semester	Frühjahrssemester 2024
Durchführender Fachbereich	Gesundheitswissenschaften
Studienstufe	Master
Termin/e	Di, 20.02.2024, 12:30 - 14:00 Uhr, 3.A05 Mi, 21.02.2024, 14:15 - 16:00 Uhr, HS 6 Di, 27.02.2024, 12:30 - 14:00 Uhr, 3.A05 Mi, 28.02.2024, 14:15 - 16:00 Uhr, HS 6 Di, 05.03.2024, 12:30 - 14:00 Uhr, 3.A05 Mi, 06.03.2024, 14:15 - 16:00 Uhr, HS 6 Di, 12.03.2024, 12:30 - 14:00 Uhr, 3.A05 Mi, 13.03.2024, 14:15 - 16:00 Uhr, HS 6 Di, 19.03.2024, 12:30 - 14:00 Uhr, 3.A05 Mi, 20.03.2024, 14:15 - 16:00 Uhr, HS 6 Di, 26.03.2024, 12:30 - 14:00 Uhr, 3.A05 Mi, 27.03.2024, 14:15 - 16:00 Uhr, HS 6 Di, 09.04.2024, 12:30 - 14:00 Uhr, 3.A05 Mi, 10.04.2024, 14:15 - 16:00 Uhr, HS 6 Di, 16.04.2024, 12:30 - 14:00 Uhr, 3.A05 Mi, 17.04.2024, 14:15 - 16:00 Uhr, HS 6 Di, 23.04.2024, 12:30 - 14:00 Uhr, 3.A05 Mi, 24.04.2024, 14:15 - 16:00 Uhr, HS 6 Di, 30.04.2024, 12:30 - 14:00 Uhr, 3.A05 Mi, 01.05.2024, 14:15 - 16:00 Uhr, HS 6 Di, 07.05.2024, 12:30 - 14:00 Uhr, 3.A05 Mi, 08.05.2024, 14:15 - 16:00 Uhr, HS 6 Di, 14.05.2024, 12:30 - 14:00 Uhr, 3.A05 Mi, 15.05.2024, 14:15 - 16:00 Uhr, HS 6 Di, 21.05.2024, 12:30 - 14:00 Uhr, 3.A05 Mi, 22.05.2024, 14:15 - 16:00 Uhr, HS 6 Di, 28.05.2024, 12:30 - 14:00 Uhr, 3.A05 Mi, 29.05.2024, 14:15 - 16:00 Uhr, HS 6 Mi, 12.06.2024, 08:15 - 09:45 Uhr, HS 9 (Prüfung) Mo, 27.01.2025, 08:15 - 09:45 Uhr, HS 9 (Wiederholungsprüfung)
Umfang	4 Semesterwochenstunden
Inhalt	Building on the fundamentals of probability and inferential statistics, the course introduces key methods used in modern quantitative research. Students learn how to carry out an empirical analysis, going beyond simple descriptive statistics and hypothesis testing. Topics include linear regression, the analysis of panel data, discrete dependent variables, and causal inference. Numerous examples and computer tutorials offer hands-on experiences in utilizing the methods.The distinctive feature of the course is a combination of traditional lecture style teaching methods, tutorials, and online activities, including video lectures, online tutorials, and the interactive analysis of a real-world dataset.
Lernziele	The objectives of this course are: (i) to deepen your understanding of inferential statistics (ii) to learn the basic methodology of modern quantitative research (iii) to acquire the skills to plan and execute your own empirical project The course focuses on applied quantitative tools, i.e., the use of real data (drawn from the Swiss Household Panel) and the application of statistical software (Stata) to practice the discussed methods will be an integral part of the learning experience.
Sprache	Englisch
Begrenzung	This course is a "Advanced Research Methods" course
Anmeldung	https://elearning.hsm-unilu.ch/course/view.php?id=690
Prüfung	Grading will be based on a final written exam (70%) and an individualized homework assignment (30%). The homework assignment consists of three tasks to be solved based on the computer labs. Details on the tasks will be communicated via the e-learning platform. An overall grade of 4.0, or higher, is required to successfully complete the course. In case of a grade lower than 4.0, repetition during the next examination period consists of a written exam only.
Abschlussform / Credits	Schriftliche Prüfung, Schriftliche Arbeit / 6 Credits
Hinweise	Teaching methods: Blended learning with lectures, tutorials, and class/online activities.
Hörer-/innen	Ja
Kontakt	stefan.boes@unilu.ch / noel.ackermann@unilu.ch / tess.bardy@unilu.ch
Material	The teaching material is based on slides, videos, online tutorials, selected book chapters and specific training datasets.
Literatur	References and readings will be provided on the e-learning platform moodle.