[ 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
Detailed information
Pre-requisites (*)keine
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.
Subject Base knowledge in descriptive statistics, probability theory and inductive statistics
Criteria for evaluation Homework assignments and a final examination
  • Lecture by instructor
  • Discussion of the homework assignments
  • Working with data using EXCEL
Language German
Study material Quatember, A. (2017). Statistik ohne Angst vor Formeln. 5. Auflage, Pearson, Hallbergmoos. (in German)
Changing subject? No
Further information In KUSSS students find EXCEL-Learning and simulation files and the collection of homework examples including the course rules
Earlier variants They also cover the requirements of the curriculum (from - to)
1MSTK: KS Introduction to Statistical Methods (2007W-2015S)
On-site course
Maximum number of participants 200
Assignment procedure Assignment according to priority
This course is additionally offered in the following versions:
MuSSS Linz    
MuSSS Linz 2023SS
Number obligatory dates     0    
MuSSS assistance     Astrid Horejs    
Number participants (min/max)     25 / 200    
Course fee     € 36,00    
Online materials and media     Powerpoint slides with audio commentary, Exercises (compulsory and optional), Excel-learning-files. The accompanying Moodle-course can be found in JKU Moodle.    
Book from onlineshop     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    
Wed08.03.202318:30 - 19:15--Zoom - Tutorium (Alle Tutorien sind ein Angebot, keine Pflicht)
Wed15.03.202318:30 - 19:15--Zoom - Tutorium
Wed22.03.202318:30 - 19:15--Zoom - Tutorium
Wed29.03.202318:30 - 19:15--Zoom - Tutorium
Wed19.04.202318:30 - 19:15--Zoom - Tutorium
Wed26.04.202318:30 - 19:15--Zoom - Tutorium
Wed10.05.202318:30 - 19:15--Zoom - Tutorium
Wed17.05.202318:30 - 19:15--Zoom - Tutorium
Wed24.05.202318:30 - 19:15--Zoom - Tutorium
Wed07.06.202318:30 - 19:15--Zoom - Tutorium
Wed14.06.202318:30 - 19:15--Zoom - Tutorium
Wed21.06.202318:30 - 19:15--Zoom - Tutorium
Wed28.06.202318:30 - 19:15--Fragestunde zur Klausur (via Zoom)
Fri30.06.202317:15 - 18:45HS 1Klausur (Hörsaal wird zugeteilt)
Fri30.06.202317:15 - 18:45HS 2Klausur (Hörsaal wird zugeteilt)
Fri30.06.202317:15 - 18:45HS 7Klausur (Hörsaal wird zugeteilt)
Wed05.07.202318:30 - 19:15--Nachbesprechung der Klausurbeispiele (via Zoom)
Wed27.09.202315:30 - 17:00HS 1Nachklausur