Course detail
Applied Statistic Methodology
FP-SmasPAcad. year: 2023/2024
The course deals with parametric and nonparametric tests, analysis of variance, categorical analysis, multivariate regression models, statistical process control methods and capability indices.
Language of instruction
Czech
Number of ECTS credits
5
Mode of study
Not applicable.
Guarantor
Department
Entry knowledge
Basic knowledge of probability theory, descriptive statistics and mathematical statistics is required.
Rules for evaluation and completion of the course
The 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 (69-60), E (59-50), F (49-0).
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.
- 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 (69-60), E (59-50), F (49-0).
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
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.
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.
Study aids
see Course literature.
Study materials available on e-learning.
Prerequisites and corequisites
Not applicable.
Basic literature
CSN ISO 8258 Shewhartovy regulační diagramy. Praha: Český normalizační institut, 1994. (CS)
KROPÁČ, J. Statistika C. 2. vyd. Brno: Akademické nakladatelství CERM, 2012. 100 s. ISBN 978-80-7204-789-5. (CS)
Studijní materiály vystavené na e-learningu. (CS)
KROPÁČ, J. Statistika C. 2. vyd. Brno: Akademické nakladatelství CERM, 2012. 100 s. ISBN 978-80-7204-789-5. (CS)
Studijní materiály vystavené na e-learningu. (CS)
Recommended reading
KROPÁČ, J. Statistika A. 4. vyd. Brno: Fakulta podnikatelská, 2011. ISBN 978-80-214-4226-9. (CS)
KROPÁČ, J. Statistika B. 2. vyd. Brno: Fakulta podnikatelská, 2009. ISBN 978-80-214-3295-6.
KUPKA, K. Statistické řízení jakosti. Pardubice: TriloByte Statistical Software, 1997. ISBN 80-238-1818-X.
MONTGOMERY, D.C. Introduction to Statistical Quality Control. 6 ed. John Wiley & Sons, 2005. ISBN 978-0-470-16992-6.
TOŠENOVSKÝ, J. a NOSKIEVIČOVÁ, D. Statistické metody pro zlepšování jakosti. 1.vyd. Ostrava: Montanex, 2000. ISBN 80-7225-040-X.
KROPÁČ, J. Statistika B. 2. vyd. Brno: Fakulta podnikatelská, 2009. ISBN 978-80-214-3295-6.
KUPKA, K. Statistické řízení jakosti. Pardubice: TriloByte Statistical Software, 1997. ISBN 80-238-1818-X.
MONTGOMERY, D.C. Introduction to Statistical Quality Control. 6 ed. John Wiley & Sons, 2005. ISBN 978-0-470-16992-6.
TOŠENOVSKÝ, J. a NOSKIEVIČOVÁ, D. Statistické metody pro zlepšování jakosti. 1.vyd. Ostrava: Montanex, 2000. ISBN 80-7225-040-X.
Elearning
eLearning: currently opened course
Classification of course in study plans
- Programme MGR-SRP Master's 1 year of study, winter semester, compulsory
Type of course unit
Lecture
13 hod., optionally
Teacher / Lecturer
Syllabus
Topics of lectures are the following:
1. Parametric statistical tests: t-test, two sample t-test and F-test
2. Kolmogorov-Smirnov test, Pearson test and Shapiro-Wilk test
3. Analysis of variance (ANOVA): one factor and two factor ANOVA
4. Nonparametric statistical tests: one sample tests
5. Nonparametric statistical tests: two sample tests
6. Nonparametric ANOVA
7. Multivariate regression models
8. Multivariate regression models: classical assumptions
9. Categorical analysis
10. Statistical Process Control
11. Control charts for measurement control
12. Control charts for comparison control
13. Process Capability Index
1. Parametric statistical tests: t-test, two sample t-test and F-test
2. Kolmogorov-Smirnov test, Pearson test and Shapiro-Wilk test
3. Analysis of variance (ANOVA): one factor and two factor ANOVA
4. Nonparametric statistical tests: one sample tests
5. Nonparametric statistical tests: two sample tests
6. Nonparametric ANOVA
7. Multivariate regression models
8. Multivariate regression models: classical assumptions
9. Categorical analysis
10. Statistical Process Control
11. Control charts for measurement control
12. Control charts for comparison control
13. Process Capability Index
Exercise
26 hod., compulsory
Teacher / Lecturer
Syllabus
The topics of exercises correspond to the topics of lectures.
Elearning
eLearning: currently opened course