Studienhandbuch | VL Probability Theory

Inhalt

^(*) Unfortunately this information is not available in english.

Workload	Education level	Study areas	Responsible person	Hours per week	Coordinating university
5 ECTS	B1 - Bachelor's programme 1. year	Statistics	Andreas Futschik	4 hpw	Johannes Kepler University Linz

Detailed information

Pre-requisites

^(*)keine

Original study plan

Bachelor's programme Statistics and Data Science 2025W

Learning Outcomes

Competences
The courses VL and UE Wahrscheinlichkeitsrechnung form an inseparable didactic unit. The learning outcomes described below are achieved through the interaction of the two courses: Students can deal with probabilities and distributions and carry out one- and multidimensional probability calculations.

Skills	Knowledge
Knowing and understanding the basic terminology, rules and theorems of elementary probability theory (k1,k2) Knowing the important distributions in view of statistical applications (k1) Knowledge of and ability to compute summaries such as moments (k2) Develop the ability to solve problems involving probabilities (k3, k6)	Combinatorics and elementary probability Discrete and continuous random variables and their distributions Moments and quantiles Multivariate distributions Covariance and correlation Sampling distributions Laws of large numbers and central limit theorem

Criteria for evaluation

Exam

Methods

Lecture

Language

German

Study material

Robert Hafner, Wahrscheinlichkeitsrechnung und Statistik
George Casella and Roger Berger, Statistical Inference

Changing subject?

Corresponding lecture

^(*)4MSW1V: VL Wahrscheinlichkeitsrechnung I (4ECTS)

On-site course
Maximum number of participants	100
Assignment procedure	Assignment according to priority