Course detail
Mathematics II
FSI-9MA2 Acad. year: 2022/2023 Both semester
Graphic analysis. Stratification. Multi-vari analysis. Multidimensional regression analysis, ANOVA, Simple sorting, double sorting, interaction. Category analysis.
Language of instruction
Czech
Supervisor
Department
Learning outcomes of the course unit
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.
Prerequisites
Rudiments of descriptive statistics, probability theory and mathematical statistics.
Planned learning activities and teaching methods
The course is taught through consultations to explanation of basic principles and theories of the discipline.
Assesment methods and criteria linked to learning outcomes
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.
Aims
Familiarization of students with multidimensional data evaluation. Focused primarily on multidimensional regression analysis, ANOVA and categorical analysis with real-world applications in technical practice.
Specification of controlled education, way of implementation and compensation for absences
Teaching is a form of consultation.
The study programmes with the given course
Programme D-IME-K: Applied Mechanics, Doctoral, recommended course
Programme D-IME-P: Applied Mechanics, Doctoral, recommended course
Type of course unit
Lecture
20 hours, optionally
Syllabus
1. Graphic analysis.
2. Stratification.
3. Multi-vari analysis.
4. ANOVA.
5. Fixed and random effects model.
6. One-way analysis.
7. Two-way analysis.
8. Interaction.
9. Tukey's method
10 Scheffe's method.