Objective of the course – aims of the course unit:
To provide the students with knowledge needed for sophisticated applications of statistical methods.
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Objective of the course – learning outcomes and competences:
n. a.
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Prerequisites:
Subjects taught in the course DA52, DA62 - Probability and mathematical statistics
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Course contents (annotation):
- multidimensional normal distribution, conditional probability distribution
- regression function
- linear regression model
- nonlinear regression model
- analysis of variance
- factor analysis
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Teaching methods and criteria:
n. a.
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Assesment methods and criteria linked to learning outcomes:
Requirements for successful completion of the subject are specified by guarantor’s regulation updated for every academic year.
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Course curriculum:
1. Multidimensional normal distribution, conditional probability distribution.
2. Regression function.
3. - 5. Linear regression model.
5.-7. General linear regression model.
8. Singular linear regression model.
9.-10. Analysis of variance.
11.-12.Factor analysis.
13. Nonlinear regression model.
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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.
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Recommended reading:
ANDĚL, J.: Matematická statistika. SNTL/ALFA Praha 1978 HEBÁK, P., HUSTOPECKÝ, J., MALÁ, I: Vícerozměrné statistické metody 1,2.3. INFORMATORIUM PRAHA 2007 ANDĚL, J.: Statistické metody. MATFYZPRESS PRAHA 2007 MELOUN, M., MILITKÝ, J.: Statistické zpracování experimentálních dat. PLUS Praha 1994 WALPOLE, R.E., MYERS, R.H.: Probability and Statistics for Engineers and Scientists. Macmillan Publishing Company New York 1990
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