Mathematical Methods of Experimental Data Processing
Module designation
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Lecturer
Language
Type of teaching, contact hours
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Recommended prerequisites
Module objectives/intended
learning outcomes
Content, hours
Assessment, forms of
examination
Mathematical Methods of Experimental Data Processing
Bachelor degree
Ilya I. Ogol
Russian, English
Lectures 36
Labs 36
Self study 72
TOTAL 144
5 ECTS
Computer Science, Calculus
Getting skills and knowledge in the field of data
processing: creating mathematical models and decisionmaking based on experimental data
By the end of the course the student will know:
Basic statistical tool for data analysis;
The students will be able to:
Make decision and provide evidence based on
experimental data
The students will have the experience in:
Performing statistical analysis using special software
packages
Topic 1 Introduction to statistic (lectures 2, labs 2)
Topic 2 Descriptive statistics (lectures 4, labs 4)
Topic 3 Student’s t-tests (lectures 4, labs 4)
Topic 4 Correlation analysis (lectures 4, labs 4)
Topic 5 Regression analysis (lectures 8, labs 8)
Topic 6 Analysis of variance (lectures 6, labs 6)
Topic 7 Nonparametric methods(lectures 4, labs 4)
Topic 8 Design of experiment (lectures 4, labs 4)
Exam: test