Czech

Not applicable.

Institute of Mathematics and Descriptive Geometry (MAT)

Students will achieve the subject's objective learning how to analyse statistical data focusing on solutions of systems of "unsolvable" linear equations minimising errors.

Basics of the theory of functions of one and several real variables (derivative, partial derivative, limit, continuous functions, graphs of functions). Basic operations with matrices and vectors.

Not applicable.

Not applicable.

Requirements for successful completion of the subject are specified by guarantor’s regulation updated for every academic year.

1. Continuous and discrete random variable (vector). Transformed random variables
2. Dependent and independent random variables. Numeric characteristics of random variables and vectors. Correlation coefficient.
3. Random sampling, statistic.
4. Systems of linear equations. Matrix equations.
5. Eigenvalues of matrices.
6. Quadratic forms and their classification. Symmetric matrices.
7. Rank of a matrix. Skeleton decomposition of a matrix.
8. Right and left inverse to a matrix. Pseudo-inverse to a matrix.
9. Solutions of systems of linear equations using inverse matrices.
10. Solving "unsolvable" systems of linear equations with minimum errors.

Not applicable.

Give the students a basic understanding of the theory of probability. Students should be able to interpret the basics of mathematical statistics.
Teach the students how to evaluate data focussing on finding solutions to "unsolvable" systems of linear equations with minimum errors.

Extent and forms are specified by guarantor’s regulation updated for every academic year.

Not applicable.

Not applicable.

KOUTKOVÁ, H., MOLL, I.: Úvod do pravděpodobnosti a matematické statistiky. Akademické nakladatelství CERM, s.r.o., 2001. (CS)

Huaan, Fan: Theory of Errors and Least Squares Adjustment. Royal Institute of Technology, Stockholm, Sweden, 2003. ISBN 91-7170-200-8. (EN)