MLU
Vorlesung: Issues in Economic Data Science: High Quality Research Data - Details
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Veranstaltungsname Vorlesung: Issues in Economic Data Science: High Quality Research Data
Semester WS 2020/21
Aktuelle Anzahl der Teilnehmenden 12
erwartete Teilnehmendenanzahl 20
Heimat-Einrichtung Wirtschaftswissenschaftlicher Bereich - School of Economics and Business
beteiligte Einrichtungen Leibniz-Institut für Agrarentwicklung in Transformationsökonomien
Veranstaltungstyp Vorlesung in der Kategorie Offizielle Lehrveranstaltungen
Erster Termin Donnerstag, 05.11.2020 15:30 - 17:00
Teilnehmende The aim of this course is to provide students with the necessary methodological skills to obtain and handle the desired data for their scientific work/thesis. The target audience are master students, however is also open for participants at other qualification levels
Voraussetzungen •The course aims at junior researchers from the field of economics, sociology and geography. There is no specific requirement on the analytical or theoretical background of the participants.
•To adapt the curriculum to individual needs, participants will be asked to fill a short questionnaire on their research interests prior to the course.
•Various software solution like Stata, ArcGIS or SurveySolutions will be presented, but require no previous knowledge or software installation for the participants.
Leistungsnachweis Grades and course credits (5 ECTS) are allocated for completing exercises during the course and the successful submission of one essay (topics will be anounced).
Studiengänge (für) gemäß Modulverknüpfung
SWS 2
ECTS-Punkte 5

Räume und Zeiten

Keine Raumangabe
Donnerstag: 15:30 - 17:00, wöchentlich

Modulzuordnungen

Kommentar/Beschreibung

The quality of research data has strong influence on the success of any scientific work. Meanwhile, the selection, collection and processing of data influences the quality and time required for the research. This course offers guidelines to plan data strategy and thus build the fundament for a high-quality thesis. The aim of this lecture is to improve practical, basic methodological and analytical skills of participants in preparation and is thus complimentary to existent courses on statistics and econometrics.