Course detail
Analysis of Engineering Experiment
FSI-TAI-A Acad. year: 2025/2026 Summer semester
The course is aimed at the selected parts of mathematical statistics for stochastic modeling of the engineering experiments: regression models, regression diagnostics, multivariate methodsand design iof experiment. Computations are carried out using the software Minitab.
Supervisor
Department
Learning outcomes of the course unit
Prerequisites
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
Course-unit credit requirements: active participation in seminars.
Exam: Presenting a assigned project.
Attendance at seminars is controlled and the teacher decides on the compensation for absences.
Language of instruction
English
Aims
Specification of controlled education, way of implementation and compensation for absences
The study programmes with the given course
Programme N-MAI-A: Mathematical Engineering, Master's
branch ---: no specialisation, 5 credits, compulsory
Type of course unit
Lecture
26 hours, optionally
Syllabus
- Principal components
- Factor analysis.
- Cluster analysis.
- ANOVA.
- Linear regression.
- Identification of regression model, regularized regression.
- Factorial design of experiment.
- Central point, blocks, replications and randomization in DoE.
- Fractional factorial DoE.
- Response surface DoE.
- Mixture DoE.
- Logistic regression.
- Nonparametric hypotheses testing.
Computer-assisted exercise
13 hours, compulsory
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.