Studienhandbuch | VL Advanced Statistical Inference

Inhalt

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

Workload	Ausbildungslevel	Studienfachbereich	VerantwortlicheR	Semesterstunden	Anbietende Uni
4 ECTS	M1 - Master 1. Jahr	Statistik	Werner Müller	2 SSt	Johannes Kepler Universität Linz

Detailinformationen

Anmeldevoraussetzungen

^(*)keine

Quellcurriculum

Masterstudium Statistics and Data Science 2025W

Lernergebnisse

Kompetenzen
^(*)The courses VL and UE Advanced Statistical Inference form an inseparable didactic unit. The learning outcomes described below are achieved through the interaction of the two courses: Students are able to mathematically justify and possibly improve methods of advanced statistical inference, particularly asymptotics.

Fertigkeiten	Kenntnisse
^(*) Knowing and understanding of the basic problems, concepts and procedures of advanced statistical inference, particularly asymptotics (k1,k2) Classify the concepts in their historical and contemporary meaning (k1) Derive mathematical facts and theorems (k3,k4,k5) Use of the Mathematica program package (k3)	^(*) Convergence concepts Generating a random sample Asymptotic evaluation of point and interval estimators and statistical tests Delta method, efficiency, bootstrap theory Robustness Decision theory Copulas

Beurteilungskriterien

^(*)Exam

Lehrmethoden

^(*)Lecture

Abhaltungssprache

Englisch

Literatur

^(*)Casella G.and Berger R.L. (2002). Statistical Inference.

Lehrinhalte wechselnd?

Nein

Äquivalenzen

^(*)in collaboration with 951MASTPRTV14: VL Probability Theory (4 ECTS) equivalent to
5MSMS2VO: VL Mathematische Statistik II (8 ECTS)

Präsenzlehrveranstaltung
Teilungsziffer	100
Zuteilungsverfahren	Zuteilung nach Vorrangzahl