Course detail
Mathematics I
FSI-9MA1 Acad. year: 2023/2024 Both semester
Normal distribution.
Estimation of parameters.
Hypothesis testing.
Analysis of variances.
Tukey's method and Scheffe method.
Linear model.
Coefficient of correlation.
Language of instruction
Czech
Supervisor
Department
Entry knowledge
Rudiments of descriptive statistics, probability theory and mathematical statistics.
Rules for evaluation and completion of the course
Use of the above-mentioned statistical methods for solving specific problems. Specific problems are selected in agreement with the student. Student's area of study is preferred. The solved, calculated and elaborated tasks serve to evaluate the student.
Teaching is a form of consultation.
Aims
Students will acquaint with testing statistical hypotheses and with real applications of linear regression methods in technical practice. Formation of a stochastic way of thinking for the creation of mathematical models with an emphasis on engineering disciplines.
Students acquire needed knowledge from important parts of the probability theory and mathematical statistics, which will enable them to evaluate and develop stochastic models of technical phenomena and processes based on these methods and realize them on PC.
The study programmes with the given course
Programme D-IME-P: Applied Mechanics, Doctoral, recommended course
Programme D-IME-K: Applied Mechanics, Doctoral, recommended course
Type of course unit
Lecture
20 hours, optionally
Syllabus
1. Collection of data.
2. Variance.
3. Pareto analysis.
4. Probability density and probability distribution.
5. Normal distribution.
6. Distribution of averages
7. Estimation of parameters.
8. Hypothesis testing.
9. Analysis of variances. One way testing,
10. Two way testing.
11. Tukey's method. Scheffe method.
12. Linear model.
13. Coefficient of correlation. Partial coefficient of correlation.
14. Statistics modelling. Monte Carlo method.