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040132 UE Statistics 1 (2023W)
Continuous assessment of course work
Labels
Summary
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Mo 11.09.2023 09:00 to Fr 22.09.2023 12:00
- Deregistration possible until Fr 20.10.2023 23:59
Registration information is available for each group.
Groups
Group 1
max. 50 participants
Language: German
LMS: Moodle
Lecturers
Classes (iCal) - next class is marked with N
- Tuesday 03.10. 13:15 - 14:45 Digital
- Tuesday 10.10. 13:15 - 14:45 Digital
- Tuesday 17.10. 13:15 - 14:45 Digital
- Tuesday 24.10. 13:15 - 14:45 Digital
- Tuesday 31.10. 13:15 - 14:45 Digital
- Tuesday 07.11. 13:15 - 14:45 Digital
- Tuesday 14.11. 13:15 - 14:45 Digital
- Tuesday 21.11. 13:15 - 14:45 Digital
- Tuesday 28.11. 13:15 - 14:45 Digital
- Monday 11.12. 11:30 - 13:00 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Monday 11.12. 13:15 - 14:45 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Aims, contents and method of the course
Reading list
Slides by F. Huber from his lecture from summer term 2023.
Lecture notes by E. Reschenhofer on his lecture from the summer term 2016.
Lecture notes by E. Reschenhofer on his lecture from the summer term 2016.
Group 2
max. 50 participants
Language: German
LMS: Moodle
Lecturers
Classes (iCal) - next class is marked with N
- Thursday 23.11. 13:15 - 14:45 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
- Monday 11.12. 13:15 - 14:45 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Tuesday 09.01. 15:00 - 16:30 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
- Thursday 11.01. 11:30 - 13:00 Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Stock
Aims, contents and method of the course
Objectives:Exercises with respect to the basics of statistics.Contents:1. Event spaces & probability
2. Distribution function, expectation and variance
3. Discrete and continuous distributions
4. Multivariate distributions and confidence intervals
5. Statistical hypothesis testing
2. Distribution function, expectation and variance
3. Discrete and continuous distributions
4. Multivariate distributions and confidence intervals
5. Statistical hypothesis testing
Reading list
Slides von F. Huber aus seiner Vorlesung aus dem Sommersemester 2023.
Skripten von E. Reschenhofer zu seiner Vorlesung aus dem Sommersemester 2016.
Skripten von E. Reschenhofer zu seiner Vorlesung aus dem Sommersemester 2016.
Group 3
max. 50 participants
Language: German
LMS: Moodle
Lecturers
Classes (iCal) - next class is marked with N
- Tuesday 03.10. 15:00 - 16:30 Digital
- Tuesday 10.10. 15:00 - 16:30 Digital
- Tuesday 17.10. 15:00 - 16:30 Digital
- Tuesday 24.10. 15:00 - 16:30 Digital
- Tuesday 31.10. 15:00 - 16:30 Digital
- Tuesday 07.11. 15:00 - 16:30 Digital
- Tuesday 14.11. 15:00 - 16:30 Digital
- Tuesday 21.11. 15:00 - 16:30 Digital
- Tuesday 28.11. 15:00 - 16:30 Digital
- Monday 11.12. 13:15 - 14:45 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Thursday 11.01. 15:00 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Aims, contents and method of the course
Objectives:Exercises with respect to the basics of statistics.Contents:1. Event spaces & probability
2. Distribution function, expectation and variance
3. Discrete and continuous distributions
4. Multivariate distributions and confidence intervals
5. Statistical hypothesis testingMethods:Completely onine via Moodle.
2. Distribution function, expectation and variance
3. Discrete and continuous distributions
4. Multivariate distributions and confidence intervals
5. Statistical hypothesis testingMethods:Completely onine via Moodle.
Reading list
Slides by F. Huber from his lecture from summer term 2023.
Lecture notes by E. Reschenhofer on his lecture from the summer term 2016.
Lecture notes by E. Reschenhofer on his lecture from the summer term 2016.
Group 4
max. 50 participants
Language: German
LMS: Moodle
Lecturers
Classes (iCal) - next class is marked with N
- Tuesday 03.10. 16:45 - 18:15 Digital
- Tuesday 10.10. 16:45 - 18:15 Digital
- Tuesday 17.10. 16:45 - 18:15 Digital
- Tuesday 24.10. 16:45 - 18:15 Digital
- Tuesday 31.10. 16:45 - 18:15 Digital
- Tuesday 07.11. 16:45 - 18:15 Digital
- Tuesday 14.11. 16:45 - 18:15 Digital
- Tuesday 21.11. 16:45 - 18:15 Digital
- Tuesday 28.11. 16:45 - 18:15 Digital
- Monday 11.12. 13:15 - 14:45 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Thursday 11.01. 16:45 - 18:15 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Aims, contents and method of the course
The aim of the course is to provide to students elementary knowledges in probability and statistics so that they gain practical skills in statistical problem solving.Probability of events
Discrete random variables
Continuous random variables
Parametric distribution
Statistical inference.
Discrete random variables
Continuous random variables
Parametric distribution
Statistical inference.
Reading list
Slides by F. Huber from his lecture from summer term 2023.
Lecture notes by E. Reschenhofer on his lecture from the summer term 2016.
Lecture notes by E. Reschenhofer on his lecture from the summer term 2016.
Group 5
Anmeldephase NEU für Gruppe 5: https://uspace.univie.ac.at/web/studium/anmeldung/-/as-studierende-registrierung/lv/040132/5/2023W
max. 50 participants
Language: German
LMS: Moodle
Lecturers
Classes (iCal) - next class is marked with N
- Monday 02.10. 11:30 - 13:00 Digital
- Monday 09.10. 11:30 - 13:00 Digital
- Monday 16.10. 11:30 - 13:00 Digital
- Monday 23.10. 11:30 - 13:00 Digital
- Monday 30.10. 11:30 - 13:00 Digital
- Monday 06.11. 11:30 - 13:00 Digital
- Monday 13.11. 11:30 - 13:00 Digital
- Monday 20.11. 11:30 - 13:00 Digital
- Monday 27.11. 11:30 - 13:00 Digital
- Monday 11.12. 13:15 - 14:45 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Aims, contents and method of the course
The aim of the course is to provide to students elementary knowledges in probability and statistics so that they gain practical skills in statistical problem solving.Probability of events
Discrete random variables
Continuous random variables
Parametric distribution
Statistical inference.
Discrete random variables
Continuous random variables
Parametric distribution
Statistical inference.
Reading list
Slides by F. Huber from his lecture from summer term 2023.
Lecture notes by E. Reschenhofer on his lecture from the summer term 2016.
Lecture notes by E. Reschenhofer on his lecture from the summer term 2016.
Information
Assessment and permitted materials
Midterm in the 4. Session.
Endterm at the end of the semester.
Presentation and marking of excercises.
Endterm at the end of the semester.
Presentation and marking of excercises.
Minimum requirements and assessment criteria
The final grade is determined as follows:
Midterm: 30%
Endterm: 30%
Marked exercises: 30%
Presentations: 10%For a passing grade 50% of all points on the mid- and endterm combined are necessary. Additionally at least 50% of exercises have to marked.
Midterm: 30%
Endterm: 30%
Marked exercises: 30%
Presentations: 10%For a passing grade 50% of all points on the mid- and endterm combined are necessary. Additionally at least 50% of exercises have to marked.
Examination topics
Contents of the topics covered
Association in the course directory
Last modified: Th 04.01.2024 12:05
2. Distribution function, expectation and variance
3. Discrete and continuous distributions
4. Multivariate distributions and confidence intervals
5. Statistical hypothesis testing