Course detail
Models of regression
FAST-DAB037Acad. year: 2020/2021
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.
Supervisor
Department
Institute of Mathematics and Descriptive Geometry (MAT)
Learning outcomes of the course unit
Not applicable.
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.
Co-requisites
Not applicable.
Recommended optional programme components
Not applicable.
Recommended or required reading
Not applicable.
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. 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.
Aims
To provide the students with knowledge needed for sophisticated applications of statistical methods.
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.
Classification of course in study plans
- Programme DPC-S Doctoral, 2. year of study, winter semester, 10 credits, compulsory-optional
- Programme DPA-S Doctoral, 2. year of study, winter semester, 10 credits, compulsory-optional
- Programme DKA-S Doctoral, 2. year of study, winter semester, 10 credits, compulsory-optional
- Programme DKC-S Doctoral, 2. year of study, winter semester, 10 credits, compulsory-optional
- Programme DPA-E Doctoral, 2. year of study, winter semester, 10 credits, compulsory-optional
- Programme DPC-E Doctoral, 2. year of study, winter semester, 10 credits, compulsory-optional
- Programme DKC-E Doctoral, 2. year of study, winter semester, 10 credits, compulsory-optional
- Programme DKA-E Doctoral, 2. year of study, winter semester, 10 credits, compulsory-optional
- Programme DKC-M Doctoral, 2. year of study, winter semester, 10 credits, compulsory-optional
- Programme DPC-M Doctoral, 2. year of study, winter semester, 10 credits, compulsory-optional
- Programme DPA-M Doctoral, 2. year of study, winter semester, 10 credits, compulsory-optional
- Programme DKA-M Doctoral, 2. year of study, winter semester, 10 credits, compulsory-optional
- Programme DKC-K Doctoral, 2. year of study, winter semester, 10 credits, compulsory-optional
- Programme DPC-K Doctoral, 2. year of study, winter semester, 10 credits, compulsory-optional
- Programme DPA-K Doctoral, 2. year of study, winter semester, 10 credits, compulsory-optional
- Programme DKA-K Doctoral, 2. year of study, winter semester, 10 credits, compulsory-optional
- Programme DPC-V Doctoral, 2. year of study, winter semester, 10 credits, compulsory-optional
- Programme DKA-V Doctoral, 2. year of study, winter semester, 10 credits, compulsory-optional
- Programme DKC-V Doctoral, 2. year of study, winter semester, 10 credits, compulsory-optional
- Programme DPA-V Doctoral, 2. year of study, winter semester, 10 credits, compulsory-optional
Type of course unit
eLearning
eLearning: currently opened course