180176 KU Foundational Econometrics (2022W)
Prüfungsimmanente Lehrveranstaltung
Labels
VOR-ORT
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Mo 12.09.2022 09:00 bis Mo 19.09.2022 10:00
- Anmeldung von Fr 23.09.2022 09:00 bis Fr 30.09.2022 10:00
- Abmeldung bis Mo 31.10.2022 23:59
Details
max. 25 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
Mittwoch
05.10.
16:45 - 18:15
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Mittwoch
12.10.
16:45 - 18:15
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Mittwoch
19.10.
16:45 - 18:15
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Mittwoch
09.11.
16:45 - 18:15
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Mittwoch
16.11.
16:45 - 18:15
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Mittwoch
23.11.
16:45 - 18:15
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Mittwoch
30.11.
16:45 - 18:15
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Mittwoch
07.12.
16:45 - 18:15
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Mittwoch
14.12.
16:45 - 18:15
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Mittwoch
11.01.
16:45 - 18:15
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Mittwoch
18.01.
16:45 - 18:15
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Mittwoch
25.01.
16:45 - 18:15
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
This lecture is aimed at introducing statistical and econometric tools both from a theoretical and applied perspective. Lectures are structured such that each of the topics we discuss are illustrated (when applicable) with artificial or real datasets using the statistical software R. This serves two purposes. First, students are introduced to various methods they might encounter in research papers such that they can comment on their adequacy. Second, they can apply these methods in their own empirical research projects. The course covers introductions to the following topics:1. Descriptive statistics, visualizations of data, statistical software2. Notational conventions and linear algebra3. Probabilities and random variables4. Statistical inference5. Linear regression
Art der Leistungskontrolle und erlaubte Hilfsmittel
Grades will be determined via three aspects in the following proportions:1. Homework (total 50%): There will be two homework assignments (25% each) during the semester. These can either be solved individually or in groups of two.2. Final exam (50%): The final exam will be a take-home exam, to be solved individually. The homework assignments and the final exam are open book, that is, students may use any materials or software if it is properly referenced. Both must be handed in as a single PDF file.
Mindestanforderungen und Beurteilungsmaßstab
There are no preliminary requirements for taking this class. To achieve a positive grade, students will have to achieve both 50% of the maximum homework grade and 50% of the maximum final grade.
Prüfungsstoff
1. Descriptive statistics, visualizations of data, statistical software
2. Probabilities and random variables
3. Statistical inference
4. Linear regression
2. Probabilities and random variables
3. Statistical inference
4. Linear regression
Literatur
Materials for the lecture will in part be provided in the form of slides and computer code. These materials are loosely based on:Wooldridge, J.M., "Introductory Econometrics: A Modern Approach," South-Western CENGAGE Learning (>= 5th edition).
Zuordnung im Vorlesungsverzeichnis
Letzte Änderung: Mi 05.10.2022 16:29