040195 KU Data Analysis on Organization and Personell (MA) (2017W)
Prüfungsimmanente Lehrveranstaltung
Labels
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Fr 08.09.2017 09:00 bis Do 21.09.2017 12:00
- Abmeldung bis Sa 14.10.2017 23:59
Details
max. 30 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
Donnerstag
05.10.
09:45 - 11:15
PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag
05.10.
11:30 - 13:00
PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag
12.10.
09:45 - 11:15
PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag
12.10.
11:30 - 13:00
PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag
19.10.
09:45 - 11:15
PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag
19.10.
11:30 - 13:00
PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag
09.11.
09:45 - 11:15
PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag
09.11.
11:30 - 13:00
PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag
16.11.
09:45 - 11:15
PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag
16.11.
11:30 - 13:00
PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag
23.11.
09:45 - 16:45
Hörsaal 17 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, final essay, class attendance and participation. Grades will be reduced for absence.
Exams consist of essay type questions. 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.Passing grades can generally not be earned by students who miss more than 10% of the total class-time.
Exam review is possible during regular semester time by appointment.
Exams consist of essay type questions. 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.Passing grades can generally not be earned by students who miss more than 10% of the total class-time.
Exam review is possible during regular semester time by appointment.
Mindestanforderungen und Beurteilungsmaßstab
Goal: Upon completion of the course, students will 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.
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.
Prüfungsstoff
quiz, assignments, final essay, class attendance and participation.
Literatur
Required Texts:
Jeffrey Wooldridge, Introductory Econometrics, A Modern Approach, 4th edition, South-Western Cengage Learning Co. 2013.
Software:
The course statistical software is STATA, which is available on the computer lab. The data for the problem sets will be posted on the course Web page. You may purchase STATA through www.stata.com at an academic price but this is strictly optional.
http://www.stata.com/order/new/edu/gradplans/student-pricing/ (Small Stata 13, student version, $35 – 49).
Jeffrey Wooldridge, Introductory Econometrics, A Modern Approach, 4th edition, South-Western Cengage Learning Co. 2013.
Software:
The course statistical software is STATA, which is available on the computer lab. The data for the problem sets will be posted on the course Web page. You may purchase STATA through www.stata.com at an academic price but this is strictly optional.
http://www.stata.com/order/new/edu/gradplans/student-pricing/ (Small Stata 13, student version, $35 – 49).
Zuordnung im Vorlesungsverzeichnis
Letzte Änderung: Mo 07.09.2020 15:28
Goal: Upon completion of the course, students will 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.