Advanced Quantitative Methods

Dozent/in	Prof. Dr. Stefan Boes; Ana Cecilia Quiroga Gutierrez, MA; Noel Ackermann, MA
Veranstaltungsart	Vorlesung/Übung
Code	FS231016
Semester	Frühjahrssemester 2023
Durchführender Fachbereich	Gesundheitswissenschaften
Studienstufe	Master
Termin/e	Do, 23.02.2023, 12:30 - 14:00 Uhr, HS 10 Mo, 27.02.2023, 12:30 - 14:00 Uhr, 3.B58 Do, 02.03.2023, 12:30 - 14:00 Uhr, HS 10 Mo, 06.03.2023, 10:15 - 12:00 Uhr, HS 3 Do, 09.03.2023, 12:30 - 14:00 Uhr, HS 10 Mo, 13.03.2023, 10:15 - 12:00 Uhr, HS 3 Do, 16.03.2023, 12:30 - 14:00 Uhr, HS 10 Mo, 20.03.2023, 10:15 - 12:00 Uhr, HS 3 Do, 23.03.2023, 12:30 - 14:00 Uhr, HS 10 Mo, 27.03.2023, 10:15 - 12:00 Uhr, HS 3 Do, 30.03.2023, 12:30 - 14:00 Uhr, HS 10 Mo, 03.04.2023, 10:15 - 12:00 Uhr, HS 3 Do, 06.04.2023, 12:30 - 14:00 Uhr, HS 10 Mo, 17.04.2023, 10:15 - 12:00 Uhr, HS 3 Do, 20.04.2023, 12:30 - 14:00 Uhr, HS 10 Mo, 24.04.2023, 10:15 - 12:00 Uhr, HS 3 Do, 27.04.2023, 12:30 - 14:00 Uhr, HS 10 Mo, 01.05.2023, 10:15 - 12:00 Uhr, HS 3 Do, 04.05.2023, 12:30 - 14:00 Uhr, HS 10 Mo, 08.05.2023, 10:15 - 12:00 Uhr, HS 3 Do, 11.05.2023, 12:30 - 14:00 Uhr, HS 10 Mo, 15.05.2023, 10:15 - 12:00 Uhr, HS 3 Do, 25.05.2023, 12:30 - 14:00 Uhr, HS 10 Do, 01.06.2023, 12:30 - 14:00 Uhr, HS 10 Mo, 12.06.2023, 14:00 - 15:30 Uhr, HS 9 (Prüfung)
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 and the application of statistical software (Stata and R) to implement 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=586
Prüfung	Grading will be based on a final written exam (50%) and an individualized homework assignment with an empirical analysis (50%). Details on the homework will be provided on e-learning platform moodle. An overall grade of 4.0 or better is required for the successful completion of the course.
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 / ana.quiroga@unilu.ch / noel.ackermann@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.