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Course detail
FP-EasPAcad. year: 2024/2025
The objective of the course is to learn students with basic principles of mathematical statistics, econometric models, categorical analysis, statistical process control methods and their use in management of company processes.Students will acquire the knowledge which allows them to use statistical methods at such a theoretical and practical level which allow them to process and perform correct data evaluation and develop the awareness and abilities of students to use statistical methods to manage of company processes.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Department
Entry knowledge
Rules for evaluation and completion of the course
COURSE COMPLETIONThe course-unit credit is awarded on the following conditions (max. 40 points):- submitting answers to calculating problems and theoretical questions.
The exam (max. 60 points)- has a written form.In the first part of the exam student solves 4 examples within 80 minutes. In the second part of the exam student works out answers to 3 theoretical questions within 15 minutes.
The mark, which corresponds to the total sum of points achieved (max. 100 points), consists of:- points achieved in control tests, points achieved to calculating questions and theoretical questions,- points achieved by solving examples,- points achieved by answering theoretical questions.
The grades and corresponding points:A (100-90), B (89-80), C (79-70), D (69-61), E (59-50), F (49-0).
COURSE COMPLETION FOR STUDENTS WITH INDIVIDUAL STUDY PLANThe course-unit credit is awarded on the following conditions (max. 40 points):- submitting answers to calculating problems and theoretical questions.
Attendance at lectures is not mandatory but is recommended. Attendance at exercises is required and checked by the tutor. An excused absence of a student from seminars can be compensated for by submitting solution of alternate exercises.
Aims
Study aids
see Course literature.Study materials available on e-learning.
Prerequisites and corequisites
Basic literature
Recommended reading
Classification of course in study plans
Lecture
Teacher / Lecturer
Syllabus
Topics of lectures are the following:1. Parametric statistical tests: t-test, two sample t-test and F-test2. Kolmogorov-Smirnov test, Pearson test and Shapiro-Wilk test3. Analysis of variance (ANOVA): one factor and two factor ANOVA4. Nonparametric statistical tests: one sample tests5. Nonparametric statistical tests: two sample tests6. Nonparametric ANOVA7. Multivariate regression models8. Multivariate regression models: classical assumptions9. Categorical analysis10. Statistical Process Control11. Control charts for measurement control12. Control charts for comparison control13. Process Capability Index
Exercise