Course detail
Analysis of Engineering Experiment
FSI-TAI Acad. year: 2021/2022 Summer semester
The course is concerned with the selected parts of mathematical statistics for stochastic modeling of the engineering experiments: analysis of variance (ANOVA), regression models, nonparametric methods, multivariate methods, and probability distributions estimation. Computations are carried out using the software as follows: Statistica, Minitab, and QCExpert.
Language of instruction
Czech
Number of ECTS credits
5
Supervisor
Department
Learning outcomes of the course unit
Students acquire needed knowledge from the 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
Descriptive statistics, probability, random variable, random vector, random sample, parameters estimation, hypotheses testing, and regression analysis.
Planned learning activities and teaching methods
The course is taught through lectures explaining the basic principles and theory of the discipline. Exercises are focused on practical topics presented in lectures.
Assesment methods and criteria linked to learning outcomes
Course-unit credit requirements: active participation in seminars, mastering the subject matter, and delivery of semester assignment. Examination (written form): a practical part (3 tasks), a theoretical part (3 tasks); ECTS evaluation used.
Aims
The course objective is to make students majoring in Mathematical Engineering and Physical Engineering acquainted with important selected methods of mathematical statistics used for a technical problems solution.
Specification of controlled education, way of implementation and compensation for absences
Attendance at seminars is controlled and the teacher decides on the compensation for absences.
The study programmes with the given course
Programme N-PMO-P: Precise Mechanics and Optics, Master's, compulsory-optional
Programme N-FIN-P: Physical Engineering and Nanotechnology, Master's, compulsory
Programme M2A-P: Applied Sciences in Engineering, Master's
branch M-MAI: Mathematical Engineering, compulsory
Type of course unit
Lecture
26 hours, optionally
Teacher / Lecturer
Syllabus
1.One-way analysis of variance.
2.Two-way analysis of variance.
3.Regression model identification.
4.Nonlinear regression analysis.
5.Regression diagnostic.
6.Nonparametric methods.
7.Correlation analysis.
8.Principle components.
9.Factor analysis.
10.Cluster analysis.
11.Continuous probability distributions estimation.
12.Discrete probability distributions estimation.
13.Stochastic modeling of the engineering problems.
Computer-assisted exercise
13 hours, compulsory
Teacher / Lecturer
Syllabus
1.PC professional statistical software.
2.One-way analysis of variance.
3.Two-way analysis of variance.
4.Regression model identification. Semester work assignment.
5.Nonlinear regression analysis.
6.Regression diagnostic.
7.Nonparametric methods.
8.Correlation analysis.
9.Principle components. Factor analysis.
10.Cluster analysis.
11.Probability distributions estimation.
12.Semester works presentation I.
13.Semester works presentation II.