040217 KU Data Analysis on Organization and Personell (MA) (2018S)
Prüfungsimmanente Lehrveranstaltung
Labels
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Mi 14.02.2018 09:00 bis Mi 21.02.2018 12:00
- Abmeldung bis Mi 14.03.2018 23:59
Details
max. 30 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine
DO 08.03.2018 09.45-13.00 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
DO 15.03.2018 09.45-13.00 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.UntergeschoßDO 15.03.2018 13.15-16.30 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.UntergeschoßDO 22.03.2018 09.45-13.00 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.UntergeschoßDO 19.04.2018 09.45-13.00 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.UntergeschoßDO 26.04.2018 09.45-16.45 Seminarraum 13 Oskar-Morgenstern-Platz 1 2.Stock
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Art der Leistungskontrolle und erlaubte Hilfsmittel
Your final grade is determined by your performance on the quizzes, assignments, presentations, final essay and class participation. Passing grades can generally not be earned by students who miss more than 10% of the total class-time.
Make-up exams will not be given unless the student has a medical or other serious reason.
Students should hand in homework assignments before class on the day they are due. Assignments will be distributed in class or on line. each student must write up his or her answers separately.Exam review is possible during regular semester time by appointment.
Make-up exams will not be given unless the student has a medical or other serious reason.
Students should hand in homework assignments before class on the day they are due. Assignments will be distributed in class or on line. each student must write up his or her answers separately.Exam review is possible during regular semester time by appointment.
Mindestanforderungen und Beurteilungsmaßstab
Basic knowledge of Business Mathematics and Statistics are required.
Your final grade is determined by your performance on the quizzes, assignments, presentations, final essay and class participation.
Passing grades can generally not be earned by students who miss more than 10% of the total class-time.
Make-up exams will not be given unless the student has a medical or other serious reason.Assignments will be distributed in class or on line. each student must write up his or her answers separately.Exam review is possible during regular semester time by appointment.
Your final grade is determined by your performance on the quizzes, assignments, presentations, final essay and class participation.
Passing grades can generally not be earned by students who miss more than 10% of the total class-time.
Make-up exams will not be given unless the student has a medical or other serious reason.Assignments will be distributed in class or on line. each student must write up his or her answers separately.Exam review is possible during regular semester time by appointment.
Prüfungsstoff
quiz, assignments, presentation, final essay, class attendance and participation.
Literatur
Zuordnung im Vorlesungsverzeichnis
Letzte Änderung: Fr 31.08.2018 08:42
Goal: Upon completion of the course, students should be able to undertake regression analysis and inference on a variety of hypotheses involving cross-sectional and time series data.
This course introduces students to regression tools for analyzing data in economics, finance and related disciplines. Extensions include regression with discrete random variables, instrumental variables regression, quasi-experiments, and regression with time series data. The objective of the course is for the student to learn how to conduct – and how to critique – empirical studies in economics, finance and related fields. Accordingly, the emphasis of the course is on empirical applications. The mathematics of econometrics will be introduced only as needed and will not be a central focus.