Course detail
Mathematics I
FSI-9MA1Acad. year: 2022/2023
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, English
Mode of study
Not applicable.
Guarantor
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 and realize them on PC.
Prerequisites
Rudiments of descriptive statistics, probability theory and mathematical statistics.
Co-requisites
Not applicable.
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.
Course curriculum
Not applicable.
Work placements
Not applicable.
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.
Specification of controlled education, way of implementation and compensation for absences
Teaching is a form of consultation.
Recommended optional programme components
Not applicable.
Prerequisites and corequisites
Not applicable.
Basic literature
F. Egermayer, M. Boháč: Statistika pro techniky, SNTL, Praha 1984 (CS)
J. Anděl: Matematická statistika, SNTL/ALFA, Praha 1978 (CS)
J. Anděl: Matematická statistika, SNTL/ALFA, Praha 1978 (CS)
Recommended reading
Not applicable.
Classification of course in study plans
Type of course unit
Lecture
20 hod., optionally
Teacher / Lecturer
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.
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.