Course detail

Applied Statistic Methodology

FP-masPAcad. year: 2020/2021

The course deals with main ideas and methods of mathematical statistics, evaluation and checking the production process with methods of statistical process control and process capability index, determination of the characteristics of acceptance sampling and inventory management, basic concepts and methods of solving matrix games.

Basic contents:

Random variable, mathematical statistics, statistical process control, capability index, statistical acceptance sampling, inventory management, matrix games.

Learning outcomes of the course unit

Students will gain knowledge of mathematical statistics, will be able to evaluate and control the production process with methods of statistical process control and process capability index, to evaluate the characteristics of acceptance sampling and inventory management, to analyze conflicting decision situations.

Prerequisites

Basic knowledge of probability theory and mathematical statistics is required.

Co-requisites

Not applicable.

Recommended optional programme components

Not applicable.

Recommended or required reading

KROPÁČ, J. Statistika A. 4. vyd. Brno: Fakulta podnikatelská, 2011. ISBN 978-80-214-4226-9. (CS)
KROPÁČ, J. a K. DOUBRAVSKÝ. Statistika C. 3. roz. vyd. Brno: Akademické nakladatelství CERM, 2020. 150 s. ISBN 978-80-7623-035-4. (CS)
CSN ISO 8258 Shewhartovy regulační diagramy. Praha: Český normalizační institut, 1994. (CS)
KROPÁČ, J. Statistika B. 2. vyd. Brno: Fakulta podnikatelská, 2009. ISBN 978-80-214-3295-6. (CS)
KUPKA, K. Statistické řízení jakosti. Pardubice: TriloByte Statistical Software, 1997. ISBN 80-238-1818-X. (CS)
MONTGOMERY, D.C. Introduction to Statistical Quality Control. 6 ed. John Wiley & Sons, 2005. ISBN 978-0-470-16992-6. (EN)
TOŠENOVSKÝ, J. a D. NOSKIEVIČOVÁ. Statistické metody pro zlepšování jakosti. 1.vyd. Ostrava: Montanex, 2000. ISBN 80-7225-040-X. (CS)

Planned learning activities and teaching methods

Teaching consists of lectures that have an explanation of basic principles and methodology of the discipline, pratical problems and their sample solutions.

Exercise promote the practical knowledge of the subject presented in the lectures.

Assesment methods and criteria linked to learning outcomes

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).

Language of instruction

Czech

Work placements

Not applicable.

Course curriculum

Topics of lectures are the following:
- Discrete Random Variables
- Continuous Random Variables
- Data samples
- Statistical Process Control
- Process Capability Index
- Acceptance Sampling
- Inventory Management
- Matrix Games

The topics of exercises correspond to the topics of lectures.

Aims

The objective of the course is to learn students to work with the random variables, to work with statistical data sets, to use methods of statistical process control, process capability indexes, acceptance sampling, inventory management and analyze conflicting decision situations.

Specification of controlled education, way of implementation and compensation for absences

Attendance at lectures is not compulsory 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.

Classification of course in study plans

  • Programme MGR-IM Master's, 2. year of study, winter semester, 5 credits, compulsory

  • Programme MGR-SI Master's

    branch MGR-IM , 2. year of study, winter semester, 4 credits, compulsory

Type of course unit

 

Lecture

13 hours, optionally

Teacher / Lecturer

Exercise

26 hours, compulsory

Teacher / Lecturer

eLearning