Course detail
Analysis of Engineering Experiment
FSI-TAI-A Acad. year: 2023/2024 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
English
Number of ECTS credits
5
Supervisor
Department
Entry knowledge
Descriptive statistics, probability, random variable, random vector, random sample, parameters estimation, hypotheses testing, and regression analysis.
Rules for evaluation and completion of the course
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.
Attendance at seminars is controlled and the teacher decides on the compensation for absences.
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.
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.
The study programmes with the given course
Programme N-MAI-A: Mathematical Engineering, Master's, compulsory
Type of course unit
Lecture
26 hours, optionally
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
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.