Inhalt

[ 551GRUSESSU14 ] UE Introduction to Inferential Statistics

Versionsauswahl
Es ist eine neuere Version 2018W dieser LV im Curriculum Diploma programme Business Education 2020W 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 Christine Duller 2 hpw Johannes Kepler University Linz
Detailed information
Pre-requisites (*)UE Einführung in die Beschreibende Statistik
Original study plan Bachelor's programme Statistics 2015W
Objectives Students know basic concepts of probability theory and inferential statistics
Subject random experiment, random variable, event, (pairwise) disjunct events, complementary event, Laplace definition of probability, Kolmogorov's axioms, conditional probability, stochastic independent events

discrete distributions: probability and distribution function, graphical representation of discrete distributions,expectation and variance, Bernoulli distribution; discrete uniform, binomial and hypergeometric distribution, approximation of discrete distributions

continuous distributions: density and distribution function and their graphical representation, expectation and variance, uniform and normal distribution, approximations, central limit theorem

sample distribution, representative sample, random sample

estimation: unbiasedness, consistency, point and interval estimation for proportions (Normal approximation) and means

hypothesis testing: basic concepts, tests for proportion (Normal approximation) and means (one sample t-test), Chi-square test for independence

Criteria for evaluation homework and exam
Methods presentation by the instructor

computer work in class

presentation of homework by students and discussion

Language German
Study material C. Duller, Einführung in die Statistik mit Excel und SPSS
Changing subject? No
Corresponding lecture (*)1MSMLU29: UE Einführung in die Methodenlehre II (3 ECTS)
On-site course
Maximum number of participants 40
Assignment procedure Assignment according to priority