Quantitative Methods I

Dozent/in	Prof. Dr. Stefan Boes
Veranstaltungsart	Masterseminar
Code	FS171190
Semester	Frühjahrssemester 2017
Durchführender Fachbereich	Health Sciences and Health Policy
Studienstufe	Master
Termin/e	Di, 28.02.2017, 10:00 - 12:00 Uhr, 3.A05 Mi, 01.03.2017, 10:15 - 12:00 Uhr, 3.B58 Di, 07.03.2017, 10:00 - 12:00 Uhr, 3.A05 Mi, 08.03.2017, 10:15 - 12:00 Uhr, 3.B58 Di, 14.03.2017, 10:00 - 12:00 Uhr, 3.A05 Mi, 15.03.2017, 10:15 - 12:00 Uhr, 3.B58 Di, 21.03.2017, 10:00 - 12:00 Uhr, 3.A05 Mi, 22.03.2017, 10:15 - 12:00 Uhr, 3.B58 Di, 28.03.2017, 10:00 - 12:00 Uhr, 3.A05 Mi, 29.03.2017, 10:15 - 12:00 Uhr, 3.B58 Di, 04.04.2017, 10:00 - 12:00 Uhr, 3.A05 Mi, 05.04.2017, 10:15 - 12:00 Uhr, 3.B58 Di, 11.04.2017, 10:00 - 12:00 Uhr, 3.A05 Mi, 12.04.2017, 10:15 - 12:00 Uhr, 3.B58 Di, 25.04.2017, 10:00 - 12:00 Uhr, 3.A05 Mi, 26.04.2017, 10:15 - 12:00 Uhr, 3.B58 Di, 02.05.2017, 10:00 - 12:00 Uhr, 3.A05 Mi, 03.05.2017, 10:15 - 12:00 Uhr, 3.B58 Di, 09.05.2017, 10:00 - 12:00 Uhr, 3.A05 Mi, 10.05.2017, 10:15 - 12:00 Uhr, 3.B58 Di, 16.05.2017, 10:00 - 12:00 Uhr, 3.A05 Mi, 17.05.2017, 10:15 - 12:00 Uhr, 3.B58 Di, 23.05.2017, 10:00 - 12:00 Uhr, 3.A05 Mi, 24.05.2017, 10:15 - 12:00 Uhr, 3.B58 Di, 30.05.2017, 10:00 - 12:00 Uhr, 3.A05 Mi, 31.05.2017, 10:15 - 11:45 Uhr, 3.B58 Di, 05.09.2017, 10:15 - 11:45 Uhr, 3.A05
Weitere Daten	The course is a mandatory Basic Course.
Umfang	4 Semesterwochenstunden
Turnus	weekly
Inhalt	Based on the fundamentals of probability and inferential statistics, this module introduces the most important methods used in modern empirical research. Students will learn how to carry out an empirical project, going beyond simple descriptive statistics and hypothesis testing. Topics include linear regression, the analysis of longitudinal data, discrete dependent variables, and causal inference. Examples from the literature and computer tutorials offer hands-on experiences in utilizing the methods.
E-Learning	Teaching material is provided via the e-learning platform moodle.
Lernziele	The objectives of this module are: i) deepen your understanding of inferential statistics, (ii) learn the basic methodology of modern quantitative research, and (iii) acquire the skills to plan and execute your own empirical project.
Voraussetzungen	Statistical programming Overall grade of 4.0 or better.
Sprache	Englisch
Begrenzung	priority MA Health Sciences students
Anmeldung	Uniportal
Prüfung	Written examination 1st attempt: 31.05.2017, 10:15 - 11:45, FRO, 3.B58 Written examination 2nd attempt: 05.09.2017, 10:15 - 11:45, FRO, 3.B52
Abschlussform / Credits	Written examination (60%) and empirical project (40%) / 4 Credits
Hinweise	Blended learning with lectures, tutorials, and class/online discussions.
Hörer-/innen	Nein
Kontakt	stefan.boes@unilu.ch
Material	The teaching material is based on slides, videos, online tutorials, selected book chapters and publicly available datasets.
Literatur	Winkelmann R, Boes S (2009) Analysis of Microdata, 2e, Springer. Wooldridge JW (2013) Introductory Econometrics: A Modern Approach, 5e, Cengage Learning.