Czech

Not applicable.

Populations, samples, binomial and Poisson distributions, distributions of averages, distributions of a continuous probability, testing of hypothesis

Oral exam

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.
Empiric model, fitting, residuum, adequate model

Not applicable.

Not applicable.

B. Maroš: Empirické modely I, Brno, 1989
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

K. Zvára: Vícerozměrné statistické metody. SNTL/ALFA, Praha 1987
J. Anděl_: Matematická statistika. SNTL/ALFA, Praha 1978
B. Maroš: Empirické modely I. PC-DIR, Brno 1998

20 hours, optionally

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.