053614 VU Statistics for Data Science (2022W)
Prüfungsimmanente Lehrveranstaltung
Labels
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Mi 14.09.2022 09:00 bis Mi 21.09.2022 09:00
- Abmeldung bis Fr 14.10.2022 23:59
Details
max. 25 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
There will be no course on 11.11.2022.
Freitag
07.10.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Freitag
14.10.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Freitag
21.10.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Freitag
28.10.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Freitag
04.11.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Freitag
11.11.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Freitag
18.11.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Freitag
25.11.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Freitag
02.12.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Freitag
09.12.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Freitag
16.12.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Freitag
13.01.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Freitag
20.01.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Freitag
27.01.
15:00 - 18:15
Seminarraum 6, Währinger Straße 29 1.OG
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Art der Leistungskontrolle und erlaubte Hilfsmittel
Students have to solve homework problems and present their results in the lab session.
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 solved in order to get a passing grade.
Final Exam 40%At least half of the homework problems have to be solved 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: Mo 31.10.2022 13:28
- Statistical inference vs. statistical learning
- Bootstrap and Jackknife methods
- Linear Models and High-dimensional data
- Statistical inference for network data
- Differential PrivacyThis course is divided into lectures and lab/homework sessions.