[ 572MASTSTAK15 ] KS Introduction to Statistical Methods
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| Workload |
Education level |
Study areas |
Responsible person |
Hours per week |
Coordinating university |
| 3 ECTS |
B1 - Bachelor's programme 1. year |
Statistics |
Andreas Quatember |
2 hpw |
Johannes Kepler University Linz |
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| Detailed information |
| Pre-requisites |
(*)keine
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| Original study plan |
Bachelor's programme Business and Economics 2018W |
| Objectives |
Students will learn how to calculate simple statistics and how to analyse data regarding populations. They will acquire knowledge in inductive statistics, particularly its logical Background based on basic principles of probability theory.
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| Subject |
Base knowledge in descriptive statistics, probability theory and inductive statistics
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| Criteria for evaluation |
Homework assignments and a final examination
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| Methods |
- Lecture by instructor
- Discussion of the homework assignments
- Working with data using EXCEL
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| Language |
German |
| Study material |
Quatember, A. (2017). Statistik ohne Angst vor Formeln. 5. Auflage, Pearson, Hallbergmoos. (in German)
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| Changing subject? |
No |
| Further information |
In KUSSS students find EXCEL-Learning and simulation files and the collection of homework examples including the course rules
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| Earlier variants |
They also cover the requirements of the curriculum (from - to)
1MSTK: KS Introduction to Statistical Methods (2007W-2015S)
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| On-site course |
| Maximum number of participants |
200 |
| Assignment procedure |
Assignment according to priority |
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| MuSSS Linz 2023SS |
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| Number obligatory dates |
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0 |
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| MuSSS assistance |
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Astrid Horejs |
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| Number participants (min/max) |
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25 /
200 |
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| Course fee |
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€ 36,00 |
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| Online materials and media |
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Powerpoint slides with audio commentary, Exercises (compulsory and optional), Excel-learning-files. The accompanying Moodle-course can be found in JKU Moodle. |
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| Book from onlineshop |
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Statistik ohne Angst vor Formeln (fünfte Auflage 2017 - Quatember - Pearson Verlag), available at the price of € 24,95 at ÖH-Shop, available from course assignment |
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| Dates |
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| Day | Date | Time | Room | Topic |
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| Wed | 08.03.2023 | 18:30 - 19:15 | -- | Zoom - Tutorium (Alle Tutorien sind ein Angebot, keine Pflicht) | | Wed | 15.03.2023 | 18:30 - 19:15 | -- | Zoom - Tutorium | | Wed | 22.03.2023 | 18:30 - 19:15 | -- | Zoom - Tutorium | | Wed | 29.03.2023 | 18:30 - 19:15 | -- | Zoom - Tutorium | | Wed | 19.04.2023 | 18:30 - 19:15 | -- | Zoom - Tutorium | | Wed | 26.04.2023 | 18:30 - 19:15 | -- | Zoom - Tutorium | | Wed | 10.05.2023 | 18:30 - 19:15 | -- | Zoom - Tutorium | | Wed | 17.05.2023 | 18:30 - 19:15 | -- | Zoom - Tutorium | | Wed | 24.05.2023 | 18:30 - 19:15 | -- | Zoom - Tutorium | | Wed | 07.06.2023 | 18:30 - 19:15 | -- | Zoom - Tutorium | | Wed | 14.06.2023 | 18:30 - 19:15 | -- | Zoom - Tutorium | | Wed | 21.06.2023 | 18:30 - 19:15 | -- | Zoom - Tutorium | | Wed | 28.06.2023 | 18:30 - 19:15 | -- | Fragestunde zur Klausur (via Zoom) | | Fri | 30.06.2023 | 17:15 - 18:45 | HS 1 | Klausur (Hörsaal wird zugeteilt) | | Fri | 30.06.2023 | 17:15 - 18:45 | HS 2 | Klausur (Hörsaal wird zugeteilt) | | Fri | 30.06.2023 | 17:15 - 18:45 | HS 7 | Klausur (Hörsaal wird zugeteilt) | | Wed | 05.07.2023 | 18:30 - 19:15 | -- | Nachbesprechung der Klausurbeispiele (via Zoom) | | Wed | 27.09.2023 | 15:30 - 17:00 | HS 1 | Nachklausur |
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