Course detail
Mathematics II
FSI-9MA2Acad. year: 2024/2025
Graphic analysis. Stratification. Multi-vari analysis. Multidimensional regression analysis, ANOVA, Simple sorting, double sorting, interaction. Category analysis.
Language of instruction
Czech
Mode of study
Not applicable.
Guarantor
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.
Teaching is a form of consultation.
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.
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.
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.
Study aids
Not applicable.
Prerequisites and corequisites
Not applicable.
Basic literature
D. C. Montgomery: Design of experiments, John Wiley & Sons, NY 1991 (EN)
Recommended reading
Not applicable.
Classification of course in study plans
Type of course unit
Lecture
20 hod., optionally
Teacher / Lecturer
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.
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.