602.574 (24S) BA3: Data Analytics
Überblick
- Lehrende/r
- LV-Titel englisch BA3: Data Analytics
- LV-Art Vorlesung-Kurs (prüfungsimmanente LV )
- LV-Modell Blended-Learning-Lehrveranstaltung
- Semesterstunde/n 2.0
- ECTS-Anrechnungspunkte 4.0
- Anmeldungen 22
- Organisationseinheit
- Unterrichtssprache Englisch
- mögliche Sprache/n der Leistungserbringung Englisch
- LV-Beginn 12.03.2024
- eLearning zum Moodle-Kurs
-
Anmerkungen
Please send any email concerning this course to: iopd-office@aau.at
Zeit und Ort
LV-Beschreibung
Intendierte Lernergebnisse
Students have a solid understanding of graphical models for causal inference, and impact evaluation. After completing this course, students can independently apply the newly acquired tools to solve practically relevant problems.
Lehrmethodik inkl. Einsatz von eLearning-Tools
Online videos, in-class lectures, individual and/or group exercises
Inhalt/e
Introduction to research design
Graphical Models
Causal Inference with Experiments
Causal Inference with Controls
Impact Evaluation: Basic Definitions, Assumptions, and Randomized Experiments
Difference-in-difference Estimation
Regression Discontinuity Design
Other designs
Literatur
To be announced
Prüfungsinformationen
Prüfungsmethode/n
Written exam and/or presentations
Prüfungsinhalt/e
See course content
Beurteilungskriterien/-maßstäbe
Scores on exam and presentation.
The following rules apply to the above-mentioned performance criteria regarding the use of AI tools: The use of AI tools is allowed for creating visualizations (but not substantive content) as part of the group presentation. Students must disclose the use of AI tools and label AI-generated passages accordingly. For all other parts of the presentation as well as for the written exam, the use of AI tools is explicitly prohibited.
Beurteilungsschema
Note BenotungsschemaPosition im Curriculum
- Masterstudium Management, Economics, and Data Science
(SKZ: 946, Version: 23W.1)
-
Fach: Minitrack 1: Foundations of Business Analytics
(Wahlfach)
-
7.3 BA3: Data Analytics (
0.0h VC / 4.0 ECTS)
- 602.574 BA3: Data Analytics (2.0h VC / 4.0 ECTS) Absolvierung im 2-4. Semester empfohlen
-
7.3 BA3: Data Analytics (
0.0h VC / 4.0 ECTS)
-
Fach: Minitrack 1: Foundations of Business Analytics
(Wahlfach)