Mathematics II (FSI-9MA2)

Academic year 2020/2021
Supervisor: doc. RNDr. Libor Žák, Ph.D.  
Supervising institute: ÚM all courses guaranted by this institute
Teaching language: Czech or English
Aims of the course unit:
Familiarization of students with multidimensional data evaluation. Focused primarily on multidimensional regression analysis, ANOVA and categorical analysis with real-world applications in technical practice.
Learning outcomes and competences:
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.
Course contents:
Graphic analysis. Stratification. Multi-vari analysis. Multidimensional regression analysis, ANOVA, Simple sorting, double sorting, interaction. Category analysis.
Teaching methods and criteria:
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.
Controlled participation in lessons:
Teaching is a form of consultation.
Type of course unit:
    Lecture  10 × 2 hrs. optionally                  
Course curriculum:
    Lecture 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.
Literature - fundamental:
1. D. C. Montgomery: Design of experiments, John Wiley & Sons, NY 1991
The study programmes with the given course:
Programme Study form Branch Spec. Final classification   Course-unit credits     Obligation     Level     Year     Semester  
D-IME-P full-time study --- no specialisation -- DrEx 0 Recommended course 3 1 W