Lehrveranstaltung im Frühjahrssemester 2022

Veranstaltungsnummer
22SQ07g
Semester
FrSe 2022
Typ
Vorlesung/Übung
Max. Teilnehmeranzahl
25

Termine

Tag Zeit Rhythmus Dauer Raum
Mo. 15:00 bis 17:00 Einmalig 29.08.2022 bis 29.08.2022 Gebäude Madrid - MAD 099
Di. 15:00 bis 17:00 Einmalig 28.06.2022 bis 28.06.2022 Gebäude Oslo - OSL 044
Di. 15:00 bis 17:00 Einmalig 05.07.2022 bis 05.07.2022 Gebäude Madrid - MAD 130
Mi. 12:00 bis 14:00 Alle zwei Wochen 23.03.2022 bis 22.06.2022 Gebäude Madrid - MAD 130
Do. 10:00 bis 12:00 Wöchentlich 17.03.2022 bis 23.06.2022 Gebäude Madrid - MAD 130

Kursleitung

Telefon
+49 461 805 2512
E-Mail
claudius.graebner-radkowitsch-TextEinschliesslichBindestricheBitteEntfernen-@uni-flensburg.de
Gebäude
Gebäude Madrid
Raum
MAD 219
Straße
Munketoft 3b
PLZ / Stadt
24937 Flensburg
Zeige Personen-Details

Beschreibung

Learning goals:

You will be introduced to the statistical programming language R. At the end of the course you will be able to perform all essential steps of a quantitative data analysis in R yourself. This includes:

(i)               data acquisition and preparation,

(ii)             visualization of the data on a publication-ready level, and

(iii)           analysis of the data using both traditional statistics and regression analysis, as well as modern tools from the field of machine learning.

You will learn how to write visually appealing and reproducible reports in R Markdown and use the version control system Git for (collaborative) code development.

Type of examination:

Your final grade is composed of:

-        A mid term open book exam (50%)

-        A final open book exam (50%)

Further information:

Students will need to bring their personal laptops to class; you will need to install R, R Studio, and Git on your Laptop. All software used during this course is free and open source. All educational ressources such as textbooks are also free and open source.

 

Veranstaltungsgliederung: https://www.uni-flensburg.de/fileadmin/content/abteilungen/plurale-oekonomik/dokumente/etc/outline-datasciencer-1-0.pdf

 

Literatur

Ismai, C. & Kim, A. (2021): Statistical Inference via Data Science. Online: moderndive.com/index.html

Wickham, H. & Grolemund, G. (2017): R for Data Science. Online: r4ds.had.co.nz/index.html

Hanck, C., Arnold, M., Gerber, A. & Schmelzer, M. (2021): Introduction to Econometrics with R. Online: www.econometrics-with-r.org

Wickham, H. (2019): Advanced R. Online: adv-r.hadley.nz

More literature will be provided through the course outline [see Link above]

Studienschwerpunkte