053614 VU Statistics for Data Science (2021W)
Prüfungsimmanente Lehrveranstaltung
Labels
GEMISCHT
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Mo 13.09.2021 09:00 bis Mo 20.09.2021 09:00
- Abmeldung bis Do 14.10.2021 23:59
Details
max. 25 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
Freitag
01.10.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Freitag
08.10.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Freitag
15.10.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Freitag
22.10.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Freitag
29.10.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Freitag
05.11.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Freitag
12.11.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Freitag
19.11.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Freitag
26.11.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Freitag
03.12.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Freitag
10.12.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Freitag
17.12.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Freitag
07.01.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Freitag
14.01.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Freitag
21.01.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Freitag
28.01.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Art der Leistungskontrolle und erlaubte Hilfsmittel
Student have to solve homework problems and present their results in an interactive online class.
At the end of the semester students can choose the format of their final exam: a) oral final exam or b) take-home project.
In case a) you get 30 minutes of general questions about the course material. In case b) you have to do a 15 minutes discussion of your solutions with the lecturer.
At the end of the semester students can choose the format of their final exam: a) oral final exam or b) take-home project.
In case a) you get 30 minutes of general questions about the course material. In case b) you have to do a 15 minutes discussion of your solutions with the lecturer.
Mindestanforderungen und Beurteilungsmaßstab
Homework 60%
Final Exam 40%At least half of the homework problems have to be completed in order to get a passing grade.
Final Exam 40%At least half of the homework problems have to be completed in order to get a passing grade.
Prüfungsstoff
Option a)
The final exam will cover all the material that was discussed in lectures and homework sessions during the semester.Option b)
The final project will require you to independently solve theoretical and applied statistics problems related to what we have learned in the course.
The final exam will cover all the material that was discussed in lectures and homework sessions during the semester.Option b)
The final project will require you to independently solve theoretical and applied statistics problems related to what we have learned in the course.
Literatur
Rice, J.A. (2007): “Mathematical Statistics and Data Analysis”, Duxbury.
Zuordnung im Vorlesungsverzeichnis
Modul: SDS
Letzte Änderung: Di 28.09.2021 13:28
- Statistical inference vs. statistical learning
- Bootstrap and Jackknife methods
- High-dimensional data and inference post-model-selection
- Statistical inference for network data
- Differential PrivacyWe will try to do this course in physical presence in the lecture hall if possible. Please closely follow the Moodle course webpage to stay up to date! (coming soon)