040436 VK KFK ORPE: Data Analysis in Organization and Personnel (2016W)
Prüfungsimmanente Lehrveranstaltung
Labels
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Mo 12.09.2016 09:00 bis Do 22.09.2016 14:00
- Abmeldung bis Fr 14.10.2016 14:00
Details
max. 30 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
Donnerstag
06.10.
09:45 - 11:15
PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag
06.10.
11:30 - 13:00
PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag
13.10.
09:45 - 11:15
PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag
13.10.
11:30 - 13:00
PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag
20.10.
09:45 - 11:15
PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag
20.10.
11:30 - 13:00
PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag
27.10.
09:45 - 11:15
PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag
27.10.
11:30 - 13:00
PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag
03.11.
09:45 - 11:15
PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag
03.11.
11:30 - 13:00
PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag
10.11.
09:45 - 11:15
PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag
10.11.
11:30 - 13:00
PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag
17.11.
09:45 - 11:15
PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag
17.11.
11:30 - 13:00
PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag
24.11.
09:45 - 11:15
PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Summary: “This course emphasizes statistical methods for analyzing data used by social scientists. Topics include simple and multiple regression analyses and the various methods of detecting and correcting data problems.”
Art der Leistungskontrolle und erlaubte Hilfsmittel
Exams, Quizzes and Assignments:
Exams consist of essay type questions. Final exam is comprehensive. Make-up exams will not be given unless the student has a medical or other serious reason, in which case the student must be able to obtain a letter including a signature and telephone number. Points will be deducted for late assignments. Calculators may be used on exams, but may not be shared. All exams are closed book.
Students should hand in homework assignments before class on the day they are due. Assignments will be distributed in class or on line. Students are encouraged to work with others in the class on their problem sets, but each student must write up his or her answers separately. The maximum group size is 2.Grading Policy:
Your final grade is determined by your performance on the quizzes, assignments, final exam, class attendance and participation. Grades will be reduced for absence.
Exams consist of essay type questions. Final exam is comprehensive. Make-up exams will not be given unless the student has a medical or other serious reason, in which case the student must be able to obtain a letter including a signature and telephone number. Points will be deducted for late assignments. Calculators may be used on exams, but may not be shared. All exams are closed book.
Students should hand in homework assignments before class on the day they are due. Assignments will be distributed in class or on line. Students are encouraged to work with others in the class on their problem sets, but each student must write up his or her answers separately. The maximum group size is 2.Grading Policy:
Your final grade is determined by your performance on the quizzes, assignments, final exam, class attendance and participation. Grades will be reduced for absence.
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.
Prüfungsstoff
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 15:29