Some properties of matrices. Linear model: the Gauss-Markov theorem, confidence ellipsoids, confidence bounds, testing submodels. Nonlinear regression models: geometrical interpretation, linearization of models, iterative methods of computation of least squares estimates, the consistency and asymptotic normality of estimates.

Type of methodology: Combination of lecture and hands-on

Participants receive the certificate of attendance: Yes

Paid training activity for participants: Yes, for all

Participants prerequisite knowledge: Numerical methods (linear algebra, statistics); Domain-specific background knowledge