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Course detail

Empiric Models

Course unit code: FSI-9EMM
Academic year: 2016/2017
Year of study: Not applicable.
Semester: winter
Number of ECTS credits:
Learning outcomes of the course unit:
Empiric model, fitting, residuum, adequate model
Mode of delivery:
Not applicable.
Prerequisites:
Populations, samples, binomial and Poisson distributions, distributions of averages, distributions of a continuous probability, testing of hypothesis
Co-requisites:
Not applicable.
Recommended optional programme components:
Not applicable.
Course contents (annotation):
If the important variables for a process are known or sought but the process model is unknown, an empirical approach to model building is required. The development of empirical models represents a continuous process that involves postulation of a model, experimentation to collect empirical data, "fitting" of the model, i.e. estimation of the model coefficients, and evaluation of results. The strategy of empirical model building is described in the course.
Recommended or required reading:
K. Zvára: Vícerozměrné statistické metody. SNTL/ALFA, Praha 1987
B. Maroš: Empirické modely I, Brno, 1989
J. Anděl_: Matematická statistika. SNTL/ALFA, Praha 1978
K. Zvára: Regresní analýza. Academia, Praha 1989
D. M. Himmelblau: Process Analysis by Statistical Methods. John Wiley&Sons,New York 1969
Vícerozměrné statistické metody: Vícerozměrné statistické metody. SNTL/ALFA, Praha 1987
B. Maroš: Empirické modely I. PC-DIR, Brno 1998
Planned learning activities and teaching methods:
The course is taught through lectures explaining the basic principles and theory of the discipline.
Assesment methods and criteria linked to learning outcomes:
Oral exam
Language of instruction:
Czech, English
Work placements:
Not applicable.
Course curriculum:
Not applicable.
Aims:
If the important variables for a process are known or sought but the process model is unknown, an empirical approach to model building is required. The development of empirical models represents a continuous process that involves postulation of a model, experimentation to collect empirical data, "fitting" of the model, i.e. estimation of the model coefficients, and evaluation of results. The strategy of empirical model building is described in the course.
Specification of controlled education, way of implementation and compensation for absences:
Not applicable.

Type of course unit:

Lecture: 20 hours, optionally
Teacher / Lecturer: doc. RNDr. Bohumil Maroš, CSc.
Syllabus: 1. Linear models. Linearization of the nonlinear model.
2. Linear models with one independent variable. Least squares estimation.
3. Analysis of variance. Variances of parameters.
4. Variances of predicted values.
5. ANOVA about the adequate model.
6. Confidence intervals for parameters.
7. Locus of confidence limits.
8. Locus of tolerance limits.
9. Confidence region.
10.Linear models with several independent variables.
11.Reziduals.

The study programmes with the given course