The course covers advanced topics in probability, statistics, and observation correction theory, providing students with a comprehensive understanding of these critical areas. Learning outcomes include mastery of probability theory, statistical tests, and distribution functions, as well as the application of computational methods through programming. Students will delve into observation correction using the Least Squares method, addressing general and special cases, and learn techniques for handling large systems of normal equations. The course also covers dynamic state modeling, Kalman filter equations, and their applications. Interpolation and filtering methods, including various forms of Kriging and surface adjustments, are thoroughly explored.
- Teacher: Μαρία Τσακίρη
ECTS : 0
Language : el, en