Universität Wien

040132 UE Statistics 1 (2025W)

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

Summary

1 Pastukhov , Moodle
2 Pastukhov , Moodle
3 Guzmics , Moodle
4 Finocchio , Moodle
5 ON-SITE Pelizzari , 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

  • Thursday 02.10. 09:45 - 11:15 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 09.10. 09:45 - 11:15 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 16.10. 09:45 - 11:15 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 23.10. 09:45 - 11:15 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 30.10. 09:45 - 11:15 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 06.11. 09:45 - 11:15 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 13.11. 09:45 - 11:15 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 20.11. 09:45 - 11:15 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 27.11. 09:45 - 11:15 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Friday 28.11. 13:15 - 14:45 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 04.12. 09:45 - 11:15 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Friday 12.12. 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.

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

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.
Let 0 <= P <= 100 be the total point (Exam + Home Work + Presentation). Then
if 100 >= P >= 87.5 the Grade is 1;
if 87.5 > P >= 75 the Grade is 2;
if 75 > P >= 62.5 the Grade is 3;
if 62.5 > P >= 50 the Grade is 4;
if 50 > P >=87.5 the Grade is 5.

Reading list

Skripten von E. Reschenhofer zu seiner Vorlesung aus dem Sommersemester 2016

Group 2

max. 50 participants
Language: English
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

  • Thursday 02.10. 16:45 - 18:15 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 09.10. 16:45 - 18:15 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 16.10. 16:45 - 18:15 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 23.10. 16:45 - 18:15 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 30.10. 16:45 - 18:15 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 06.11. 16:45 - 18:15 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 13.11. 16:45 - 18:15 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 20.11. 16:45 - 18:15 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 27.11. 16:45 - 18:15 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Friday 28.11. 13:15 - 14:45 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 04.12. 16:45 - 18:15 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Friday 12.12. 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.

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

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.

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.
Let 0 <= P <= 100 be the total point (Exam + Home Work + Presentation). Then
if 100 >= P >= 87.5 the Grade is 1;
if 87.5 > P >= 75 the Grade is 2;
if 75 > P >= 62.5 the Grade is 3;
if 62.5 > P >= 50 the Grade is 4;
if 50 > P >=87.5 the Grade is 5.

Reading list

Collection of problems (available on Moodle)
Material from lecture "Statistics 1 (VO)" from Summer Semester 2024

Group 3

max. 50 participants
Language: German
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

  • Thursday 02.10. 15:00 - 16:30 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 09.10. 15:00 - 16:30 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 16.10. 15:00 - 16:30 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 23.10. 15:00 - 16:30 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 30.10. 15:00 - 16:30 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 06.11. 15:00 - 16:30 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 13.11. 15:00 - 16:30 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 20.11. 15:00 - 16:30 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 27.11. 15:00 - 16:30 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 28.11. 13:15 - 14:45 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 04.12. 15:00 - 16:30 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 11.12. 15:00 - 16:30 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Friday 12.12. 13:15 - 14:45 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 18.12. 15:00 - 16:30 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock

Aims, contents and method of the course

The aim of the course is to provide to students elementary knowledge 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

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.

Reading list

Übungsbeispiele (auf Moodle)
Unterlagen der VO "Statistik 1 (VO)" aus dem Sommersemester 2024

Group 4

max. 50 participants
Language: English
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

  • Friday 03.10. 13:15 - 14:45 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 10.10. 13:15 - 14:45 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 17.10. 13:15 - 14:45 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 24.10. 13:15 - 14:45 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 31.10. 13:15 - 14:45 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 07.11. 13:15 - 14:45 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 14.11. 13:15 - 14:45 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 21.11. 13:15 - 14:45 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 28.11. 13:15 - 14:45 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Friday 05.12. 13:15 - 14:45 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 12.12. 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.

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

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.

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: German
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

Block ab Mitte November

  • Monday 17.11. 11:30 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
  • Monday 24.11. 11:30 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
  • Monday 01.12. 11:30 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
  • Wednesday 03.12. 09:45 - 11:15 Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 10.12. 09:45 - 11:15 Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 15.12. 11:30 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
  • Wednesday 07.01. 09:45 - 11:15 Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 12.01. 11:30 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
  • Wednesday 14.01. 09:45 - 11:15 Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 19.01. 11:30 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
  • Monday 26.01. 11:30 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00

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

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.

Information

Assessment and permitted materials

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

Examination topics

Contents of the topics covered

Association in the course directory

Last modified: Tu 27.01.2026 14:25