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FAST-DAB037Acad. year: 2022/2023
Multidimensional normal distribution, conditional probability distribution. Regression function. Linear regression model. Nonlinear regression model. Analysis of variance. Factor analysis. The use of statistical systems for regression analysis.
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Number of ECTS credits
Mode of study
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Learning outcomes of the course unit
Prerequisites
Basics of the theory of probability, mathematical statistics and linear algebra - the normal distribution law, numeric characteristics of random variables and vectors and their point and interval estimates, principles of the testing of statistical hypotheses, solving a system of linear equations, inverse to a matrix.
Co-requisites
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
Course curriculum
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Aims
Specification of controlled education, way of implementation and compensation for absences
Recommended optional programme components
Prerequisites and corequisites
Basic literature
Recommended literature
Classification of course in study plans
Lecture
Teacher / Lecturer
Syllabus
1. Multidimensional normal distribution, conditional probability distribution.
2. Regression function.
3.–5. Linear regression model.
6.–7. General linear regression model.
8. Singular linear regression model.
9.–10. Analysis of variance.
11.–12.Factor analysis.
13. Nonlinear regression model.