Course detail
Probability and mathematical statistics
FAST-DA03Acad. year: 2020/2021
Continuous and discrete random variables (vectors), probability function, density function, probability, cumulative distribution, independent random variables, characteristics of distribution, transformation of random variables, conditional distribution, conditional mean, special distributions.
Random sampling, statistic, point estimate of distribution parameters and their functions, desirable properties of an estimator, estimator of correlation matrix, confidence interval for distribution parameter, fundamentals for testing hypotheses, tests of hypotheses for distribution parameters - one-sample analysis, two-sample analysis, goodness-of-fit test.
Supervisor
Department
Institute of Mathematics and Descriptive Geometry (MAT)
Learning outcomes of the course unit
Not applicable.
Prerequisites
Basics of linear algebra, differentiation, integration.
Co-requisites
Not applicable.
Recommended optional programme components
Not applicable.
Recommended or required reading
ANDĚL, J.: Statistické metody. MATFYZPRESS PRAHA 2007
KOUTKOVÁ, H.: Základy teorie odhadu. CERM Brno 2007
KOUTKOVÁ, H.: Základy testování hypotéz. CERM Brno 2007
KOUTKOVÁ, H., DLOUHÝ, O.: Sbírka příkladů z pravděpodobnosti a matematické statistiky. CERM Brno 2011
KOUTKOVÁ, H., MOLL, I.: Základy pravděpodobnosti. CERM Brno 2011
DOWDY, S., WEARDEN, S.: Statistics for research. John Wiley & sons 1982
WALPOLE, R.E., MYERS, R.H.: Probability and Statistics for Engineers and Scientists. Macmillan Publishing Company New York 1990
Planned learning activities and teaching methods
Not applicable.
Assesment methods and criteria linked to learning outcomes
Not applicable.
Language of instruction
Czech
Work placements
Not applicable.
Course curriculum
1. - 8. Continuous and discrete random variables (vectors), probability function, density function, probability, cumulative distribution, independent random variables, characteristics of distribution, transformation of random variables, conditional distribution, conditional mean, special distributions.
9. - 13. Random sampling, statistic, point estimate of distribution parameters and their functions, desirable properties of an estimator, estimator of correlation matrix, confidence interval for distribution parameter, fundamentals for testing hypotheses, tests of hypotheses for distribution parameters - one-sample analysis, two-sample analysis, goodness-of-fit test.
Aims
The correct grasp of the basic concepts and art of interpreting statistical outcomes.
Specification of controlled education, way of implementation and compensation for absences
Extent and forms are specified by guarantor’s regulation updated for every academic year.