Vorlesungsverzeichnis
Suchen Sie hier über ein Suchformular im Vorlesungsverzeichnis der Leuphana.
Lehrveranstaltungen
Inferential Statistics II (Vorlesung)
Dozent/in: Monika Tschense, Sebastian Wallot
Termin:
wöchentlich | Montag | 10:15 - 11:45 | 16.10.2023 - 02.02.2024 | C 14.027 Seminarraum
Inhalt: Quantitative methods covered in the lecture will be repeated in the seminar and practically applied by means of exercises. For independent consolidation of the methods, the students work on a weekly assignment sheet, which is handed in to the tutor. The practical exercises are done with the free open source software R (http://www.r-project.org/).
Inferential Statistics II - Group A (Übung)
Dozent/in: Monika Tschense, Sebastian Wallot
Termin:
wöchentlich | Dienstag | 12:15 - 13:45 | 24.10.2023 - 23.01.2024 | C 12.112 Seminarraum | starts in the 2nd week
Inhalt: Quantitative methods covered in the lecture will be repeated in the seminar and practically applied by means of exercises. For independent consolidation of the methods, the students work on a weekly assignment sheet, which is handed in to the tutor. The practical exercises are done with the free open source software R (http://www.r-project.org/).
Inferential Statistics II - Group B (Übung)
Dozent/in: Monika Tschense, Sebastian Wallot
Termin:
wöchentlich | Dienstag | 08:15 - 09:45 | 24.10.2023 - 23.01.2024 | C 14.103 Seminarraum | starts in the 2nd week
Inhalt: Quantitative methods covered in the lecture will be repeated in the seminar and practically applied by means of exercises. For independent consolidation of the methods, the students work on a weekly assignment sheet, which is handed in to the tutor. The practical exercises are done with the free open source software R (http://www.r-project.org/).
Inferential Statistics II - Group C (Übung)
Dozent/in: Flavia Felletti, Monika Tschense, Sebastian Wallot
Termin:
wöchentlich | Donnerstag | 12:15 - 13:45 | 26.10.2023 - 23.01.2024 | C 6.317 Seminarraum | starts in the 2nd week
Inhalt: Quantitative methods covered in the lecture will be repeated in the seminar and practically applied by means of exercises. For independent consolidation of the methods, the students work on a weekly assignment sheet, which is handed in to the tutor. The practical exercises are done with the free open source software R (http://www.r-project.org/).