[ 572MASTSTAK15 ] KS Introduction to Statistical Methods

Es ist eine neuere Version 2018W dieser LV im Curriculum Bachelor's programme Social Economics 2018W vorhanden.
(*) Unfortunately this information is not available in english.
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 2017W
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 files and the collection of homework examples including the course rules
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    
Number obligatory dates     0    
MuSSS assistance     Astrid Horejs-Kainrath    
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    
Tue02.10.201811:00 - 11:45S2 219Tutorium
Wed03.10.201812:00 - 12:45HT 177FTutorium
Tue09.10.201811:00 - 11:45S2 219Tutorium
Wed10.10.201812:00 - 12:45HT 177FTutorium
Tue16.10.201811:00 - 11:45S2 219Tutorium
Wed17.10.201812:00 - 12:45HT 177FTutorium
Tue23.10.201811:00 - 11:45S2 219Tutorium
Wed24.10.201812:00 - 12:45HT 177FTutorium
Tue30.10.201811:00 - 11:45S2 219Tutorium
Wed31.10.201812:00 - 12:45HT 177FTutorium
Tue06.11.201811:00 - 11:45S2 219Tutorium
Wed07.11.201812:00 - 12:45HT 177FTutorium
Tue13.11.201811:00 - 11:45S2 219Tutorium
Wed14.11.201812:00 - 12:45HT 177FTutorium
Tue20.11.201811:00 - 11:45S2 219Tutorium
Wed21.11.201812:00 - 12:45HT 177FTutorium
Tue27.11.201811:00 - 11:45S2 219Tutorium
Wed28.11.201812:00 - 12:45HT 177FTutorium
Tue04.12.201811:00 - 11:45S2 219Tutorium
Wed05.12.201812:00 - 12:45HT 177FTutorium
Tue11.12.201811:00 - 11:45S2 219Tutorium
Wed12.12.201812:00 - 12:45HT 177FTutorium
Tue08.01.201911:00 - 11:45S2 219Tutorium
Wed09.01.201912:00 - 12:45HT 177FTutorium
Tue15.01.201911:00 - 11:45S2 219Tutorium
Wed16.01.201912:00 - 12:45HT 177FTutorium
Tue22.01.201911:00 - 11:45S2 219Tutorium
Wed23.01.201912:00 - 12:45HT 177FTutorium
Fri25.01.201915:30 - 17:00HS 1Klausur (Hörsaal wird zugeteilt)
Fri25.01.201915:30 - 17:00HS 16Klausur (Hörsaal wird zugeteilt)
Mon28.01.201910:15 - 11:45HS 18Klausurnachbesprechung
Tue26.02.201913:45 - 15:15HS 1Nachklausur