Universität Wien

040132 UE Statistics 1 (2025S)

2.00 ECTS (1.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work

Summary

1 Nadin , Moodle
2 Nadin , Moodle
3 MIXED Grass , Moodle
4 Pastukhov , Moodle
5 Pastukhov , Moodle
6 Guzmics , Moodle
7 Guzmics , Moodle
8 REMOTE Grass , Moodle

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 information is available for each group.

Groups

Group 1

max. 50 participants
Language: English
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

  • Wednesday 05.03. 15:00 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 19.03. 15:00 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 26.03. 15:00 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 02.04. 15:00 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 09.04. 15:00 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 30.04. 15:00 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 07.05. 15:00 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 14.05. 13:15 - 14:45 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 22.05. 15:00 - 16:30 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
    Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 28.05. 15:00 - 16:30 Seminarraum 15 Oskar-Morgenstern-Platz 1 3.Stock
  • Thursday 05.06. 13:15 - 14:45 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
    Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß

Aims, contents and method of the course

The course aims to provide elementary knowledge in probability and statistics so that students may gain practical skills in statistical problem-solving.

Contents:

1. event spaces & probability
2. distribution function, expected value, and variance
3. discrete and continuous distributions
4. descriptive statistics and estimation
5. statistical hypothesis tests

Assessment and permitted materials

Endterm and/or retake at the end of the semester. Presentation and marking of exercises.

Minimum requirements and assessment criteria

The final grade is determined as follows:

Endterm: 50%
Marked exercises: 30%
Presentation: 20%

For a passing grade, 50% of all points are necessary. Additionally, at least 50% of exercises have to be marked and 50% of the endterm points must be obtained.

Examination topics

Contents of the topics covered.

Reading list

Collection of problems (available on Moodle).
Material from the lecture "Statistics 1 (VO)" from Summer Semester 2025.
Henze, N. (2008) Stochastik für Einsteiger.
Krengel, U. (2000) Einführung in die Wahrscheinlichkeitstheorie und Statistik.
Fahrmeir, L., Künstler, R., Pigeot, I., Tutz, G. (2007) Statistik: Der Weg zur Datenanalyse.
Larsen, R.J., Marx, M.L. (2012) Introduction to Mathematical Statistics and its Applications.

Group 2

max. 50 participants
Language: English
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

  • Wednesday 05.03. 13:15 - 14:45 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 19.03. 13:15 - 14:45 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 26.03. 13:15 - 14:45 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 02.04. 13:15 - 14:45 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 09.04. 13:15 - 14:45 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 30.04. 13:15 - 14:45 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 07.05. 13:15 - 14:45 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 14.05. 13:15 - 14:45 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 22.05. 15:00 - 16:30 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
    Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 28.05. 13:15 - 14:45 Seminarraum 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 05.06. 13:15 - 14:45 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
    Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß

Aims, contents and method of the course

The course aims to provide elementary knowledge in probability and statistics so that students may gain practical skills in statistical problem-solving.

Contents:

1. event spaces & probability
2. distribution function, expected value, and variance
3. discrete and continuous distributions
4. descriptive statistics and estimation
5. statistical hypothesis tests

Assessment and permitted materials

Endterm and/or retake at the end of the semester. Presentation and marking of exercises.

Minimum requirements and assessment criteria

The final grade is determined as follows:

Endterm: 50%
Marked exercises: 30%
Presentation: 20%

For a passing grade, 50% of all points are necessary. Additionally, at least 50% of exercises have to be marked and 50% of the endterm points must be obtained.

Examination topics

Contents of the topics covered.

Reading list

Collection of problems (available on Moodle).
Material from the lecture "Statistics 1 (VO)" from Summer Semester 2025.
Henze, N. (2008) Stochastik für Einsteiger.
Krengel, U. (2000) Einführung in die Wahrscheinlichkeitstheorie und Statistik.
Fahrmeir, L., Künstler, R., Pigeot, I., Tutz, G. (2007) Statistik: Der Weg zur Datenanalyse.
Larsen, R.J., Marx, M.L. (2012) Introduction to Mathematical Statistics and its Applications.

Group 3

max. 50 participants
Language: German
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

ATTENTION: On-site Endterm Test!
The endterm test will take place in the week following the last exercise session at the OMP (the exact date will be announced).
Participation must be in person on-site, there is no option for a digital endterm test.

  • Thursday 06.03. 09:45 - 11:15 Digital
  • Thursday 13.03. 09:45 - 11:15 Digital
  • Thursday 20.03. 09:45 - 11:15 Digital
  • Thursday 27.03. 09:45 - 11:15 Digital
  • Thursday 03.04. 09:45 - 11:15 Digital
  • Thursday 10.04. 09:45 - 11:15 Digital
  • Thursday 08.05. 09:45 - 11:15 Digital
  • Thursday 22.05. 15:00 - 16:30 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
    Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 05.06. 13:15 - 14:45 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
    Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß

Group 4

max. 50 participants
Language: English
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

  • Tuesday 04.03. 16:45 - 18:15 Hörsaal 16 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 11.03. 16:45 - 18:15 Hörsaal 16 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 18.03. 16:45 - 18:15 Hörsaal 16 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 25.03. 16:45 - 18:15 Hörsaal 16 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 01.04. 16:45 - 18:15 Hörsaal 16 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 08.04. 16:45 - 18:15 Hörsaal 16 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 29.04. 16:45 - 18:15 Hörsaal 16 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 22.05. 15:00 - 16:30 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
    Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 05.06. 13:15 - 14:45 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
    Hörsaal 4 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.
Contents:
1. event spaces & probability
2. distribution function, expected value and variance
3. discrete and continuous distributions
4. descriptive statistics and estimation
5. statistical hypothesis tests

Assessment and permitted materials

Endterm and/or retake at the end of the semester.
Presentation and marking of exercises.

Minimum requirements and assessment criteria

The final grade is determined as follows:
Endterm: 50%
Marked exercises: 30%
Presentations: 20%
For a passing grade, 50% of all points are necessary. Additionally, at least 50% of exercises have to marked and 50% of the endterm points must be obtained.

Examination topics

Contents of the topics covered

Reading list

Collection of problems (available on Moodle).
Material from the lecture "Statistics 1 (VO)" from Summer Semester 2025.
Henze, N. (2008) Stochastik für Einsteiger.
Krengel, U. (2000) Einführung in die Wahrscheinlichkeitstheorie und Statistik.
Fahrmeir, L., Künstler, R., Pigeot, I., Tutz, G. (2007) Statistik: Der Weg zur Datenanalyse.
Larsen, R.J., Marx, M.L. (2012) Introduction to Mathematical Statistics and its Applications.

Group 5

max. 50 participants
Language: English
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

  • Wednesday 05.03. 16:45 - 18:15 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 13.03. 11:30 - 13:00 Hörsaal 16 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 19.03. 16:45 - 18:15 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 26.03. 16:45 - 18:15 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 02.04. 16:45 - 18:15 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 09.04. 16:45 - 18:15 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 30.04. 16:45 - 18:15 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 22.05. 15:00 - 16:30 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
    Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 05.06. 13:15 - 14:45 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
    Hörsaal 4 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.

Contents:

1. event spaces & probability
2. distribution function, expected value and variance
3. discrete and continuous distributions
4. descriptive statistics and estimation
5. statistical hypothesis tests

Assessment and permitted materials

Endterm and/or retake at the end of the semester.
Presentation and marking of exercises.

Minimum requirements and assessment criteria

The final grade is determined as follows:
Endterm: 50%
Marked exercises: 30%
Presentations: 20%

For a passing grade, 50% of all points are necessary. Additionally, at least 50% of exercises have to marked and 50% of the endterm points must be obtained.

Examination topics

Contents of the topics covered

Reading list

Collection of problems (available on Moodle).
Material from the lecture "Statistics 1 (VO)" from Summer Semester 2025.
Henze, N. (2008) Stochastik für Einsteiger.
Krengel, U. (2000) Einführung in die Wahrscheinlichkeitstheorie und Statistik.
Fahrmeir, L., Künstler, R., Pigeot, I., Tutz, G. (2007) Statistik: Der Weg zur Datenanalyse.
Larsen, R.J., Marx, M.L. (2012) Introduction to Mathematical Statistics and its Applications.

Group 6

max. 50 participants
Language: German
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

  • Tuesday 04.03. 13:15 - 14:45 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 11.03. 13:15 - 14:45 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 18.03. 13:15 - 14:45 Digital
  • Tuesday 25.03. 13:15 - 14:45 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 01.04. 13:15 - 14:45 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 08.04. 13:15 - 14:45 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 29.04. 13:15 - 14:45 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 22.05. 15:00 - 16:30 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
    Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 11.06. 13:15 - 14:45 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 12.06. 15:00 - 16:30 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock

Group 7

max. 50 participants
Language: German
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

  • Tuesday 04.03. 11:30 - 13:00 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Tuesday 11.03. 11:30 - 13:00 Digital
  • Tuesday 18.03. 11:30 - 13:00 Digital
  • Tuesday 25.03. 11:30 - 13:00 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Tuesday 01.04. 11:30 - 13:00 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Tuesday 08.04. 11:30 - 13:00 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Tuesday 29.04. 11:30 - 13:00 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 22.05. 15:00 - 16:30 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
    Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 11.06. 13:15 - 14:45 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 12.06. 15:00 - 16:30 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock

Group 8

max. 50 participants
Language: German
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

ATTENTION: On-site Endterm Test!
The endterm test will take place in the week following the last exercise session at the OMP (the exact date will be announced).
Participation must be in person on-site, there is no option for a digital endterm test.

  • Thursday 06.03. 11:30 - 13:00 Digital
  • Thursday 13.03. 11:30 - 13:00 Digital
  • Thursday 20.03. 11:30 - 13:00 Digital
  • Thursday 27.03. 11:30 - 13:00 Digital
  • Thursday 03.04. 11:30 - 13:00 Digital
  • Thursday 10.04. 11:30 - 13:00 Digital
  • Thursday 08.05. 13:15 - 14:45 Digital
  • Thursday 22.05. 15:00 - 16:30 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
    Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 05.06. 13:15 - 14:45 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
    Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß

Association in the course directory

Last modified: Mo 08.09.2025 00:01