Inhalt

[ 536DASCICSV21 ] VL Introduction to Computational Statistics

Versionsauswahl
Workload Education level Study areas Responsible person Hours per week Coordinating university
3 ECTS B3 - Bachelor's programme 3. year Statistics Milan Stehlik 2 hpw Johannes Kepler University Linz
Detailed information
Original study plan Bachelor's programme Artificial Intelligence 2021W
Objectives Students learn to understand the theory and the correct application of advanced topics in computational statistics as well as to independently implement and apply selected methods.
Subject Computer arithmetic, methods of non-linear optimization and root finding, EM algorithm, pseudorandom number generation, numerical integration, Jackknife and bootstrap, permutation tests, regression, precision of statistical computation.
Criteria for evaluation Exam, Project
Methods Lecture by instructor; Discussion of the projects, where the solution is presented by the students in a project report; Independent development and application of computational statistical methods
Language English
Study material Slides. Supplementary reading (books, articles) will be announced each semester.
Changing subject? No
Corresponding lecture in combination with 536DASCICSU21: UE Introduction to Computational Statistics (1.5 ECTS) equivalent to 951STCOCSTK14 KV Computational Statistics (4 ECTS)
On-site course
Maximum number of participants -
Assignment procedure Direct assignment