Course Details

# Models of regression

DA64 course is part of 23 study plans

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D-K-E-SI (N) Winter Semester 1st year

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D-K-E-SI (N) Winter Semester 1st year

D-K-E-SI (N) Winter Semester 1st year

D-K-E-SI (N) Winter Semester 1st year

D-K-C-SI (N) Winter Semester 1st year

D-K-C-SI (N) Winter Semester 1st year

D-K-C-SI (N) Winter Semester 1st year

D-K-C-SI (N) Winter Semester 1st year

D-K-C-SI (N) Winter Semester 1st year

D-P-E-SI (N) Winter Semester 1st year

D-P-E-SI (N) Winter Semester 1st year

D-P-E-SI (N) Winter Semester 1st year

D-P-E-SI (N) Winter Semester 1st year

D-P-E-SI (N) Winter Semester 1st year

D-P-C-SI (N) Winter Semester 1st year

D-P-C-SI (N) Winter Semester 1st year

D-P-C-SI (N) Winter Semester 1st year

D-P-C-SI (N) Winter Semester 1st year

D-P-C-SI (N) Winter Semester 1st year

D-P-C-GK Winter Semester 1st year

D-K-C-GK Winter Semester 1st year

multidimensional normal distribution, conditional probability distribution
regression function
linear regression model
nonlinear regression model
analysis of variance
factor analysis
The use of statistical system STATISTICA and EXCEL for regression analysis.

Course Guarantor

RNDr. Helena Koutková, CSc.

Institute

Institute of Mathematics and Descriptive Geometry

Objective

To provide the students with knowledge needed for sophisticated applications of statistical methods.

Syllabus

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.

Prerequisites

Subjects taught in the course DA03, DA62 - Probability and mathematical statistics
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.

Language of instruction

Czech

Credits

10 credits

Semester

summer

Forms and criteria of assessment

examination

Specification of controlled instruction, the form of instruction, and the form of compensation of the absences

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

Offered to foreign students

Not to offer

Course on BUT site

https://www.vut.cz/en/students/courses/detail/255980

Lecture

13 weeks, 3 hours/week, elective

Syllabus

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.