Course detail

Applied Statistic Methodology

FP-SmasPAcad. year: 2024/2025

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.

Entry knowledge

Basic knowledge of probability theory, descriptive statistics and mathematical statistics is required.

Rules for evaluation and completion of the course

COURSE COMPLETION

The course-unit credit is awarded on the following conditions (max. 40 points):
- preparation of semester assignments (the topic of the assignments will be specified during the semester).

The exam (max. 60 points)
- has a written form with the possibility of using computer technology and consists of four computational examples and a theoretical question.

The grade, which corresponds to the total sum of points achieved (max 100 points), consists of:
- points achieved in semester assignments (max. 40 points),
- points achieved by solving examples (max. 51 points),
- points achieved by answering theoretical questions (max. 9 points).

The grade 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 such knowledge that they will be able to master statistical methods at such a theoretical and practical level that will enable them to process data and perform correct evaluation. To develop students' awareness and ability to use statistical tools as a basis for data analysis in the management of individual business activities.

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)

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.

Elearning

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
12. Process Capability Indices
13. Exploratory analysis of multivariate data

Exercise

26 hod., compulsory

Teacher / Lecturer

Syllabus

The topics of exercises correspond to the topics of lectures.

Elearning