Studienhandbuch | KV Statistics 2

Inhalt

^(*) Leider ist diese Information in Deutsch nicht verfügbar.

Workload	Ausbildungslevel	Studienfachbereich	VerantwortlicheR	Semesterstunden	Anbietende Uni
3 ECTS	M1 - Master 1. Jahr	Informatik	Thomas Forstner	2 SSt	Johannes Kepler Universität Linz

Detailinformationen

Quellcurriculum

Masterstudium Computer Science 2025W

Lernergebnisse

Kompetenzen
^(*)Students understand advanced methods of inductive statistics with focus on parametric and non-parametric statistical test procedures. They can analyze data using these methods and can interpret complex statistical methods and results.

Fertigkeiten	Kenntnisse
^(*)Students understand and can apply/calculate: parametric statistical tests for continuous data (K2, K3, K5) sample size estimation and power-analysis for parametric tests (K2, K3, K5) non-parametric statistical tests for continuous and/or rank data (K2, K3, K5) statistical tests for categorical data (K2, K3, K5) basic analysis of variance (K2, K3, K5) summary of fit statistics for binary classification systems (K2, K3, K5) odds-ratios and risk-ratios (K2, K3, K5) summary statistics for association/correlation (K2, K3, K5) partial correlation coefficients (K2, K3, K5)	^(*)Students have knowledge about: the application of complex statistical methods the interpretation of statistical results parametric and non-parametric statistical hypotheses testing using a statistical program package like R

Beurteilungskriterien

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Lehrmethoden

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Abhaltungssprache

Englisch

Literatur

^(*)slides provided by instructor, available in Moodle

Lehrinhalte wechselnd?

Nein

Sonstige Informationen

^(*)department homepage: www.systat.jku.at

Frühere Varianten

Decken ebenfalls die Anforderungen des Curriculums ab (von - bis)
INMAWKVSTA2: KV Statistik 2 (2007W-2021S)

Präsenzlehrveranstaltung
Teilungsziffer	-
Zuteilungsverfahren	Direktzuteilung