Course detail

Applied Statistics

FP-asPAcad. year: 2020/2021

Random Variables, Methods of Mathematical Statistics, Statistical Process Control, Process Capability Indices, Inventory Management.

Language of instruction

Czech

Number of ECTS credits

4

Mode of study

Not applicable.

Learning outcomes of the course unit

Students will be made familiar with the methods of mathematical statistics, to evaluate and control the production process with methods of statistical process control and process capability index, to evaluate the characteristics of inventory management.

Prerequisites

Fundamentals of probability theory and mathematical statistics.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

The course contains lectures that explain basic principles, problems and methodology of the discipline, and exercises that promote the practical knowledge of the subject presented in the lectures.

Assesment methods and criteria linked to learning outcomes

GRADED COURSE-UNIT CREDIT:
The graded course-unit credit will be awarded on the folloving conditions:
- participation in final test

The mark, which corresponds to the total sum of points achieved (max 100 points), consists of:
- points achieved in control tests,

The grades and corresponding points:
A (100-90), B (89-80), C (79-70), D (69-60), E (59-50), F (49-0).

Course curriculum

Topics of lectures are the following:
- Discrete Random Variables
- Continuous Random Variables
- Data samples
- Testing statistical hypothesis
- Regression analysis
- Statistical Process Control
- Process Capability Index
- Acceptance Sampling
- Inventory Management

The topics of exercises correspond to the topics delt with the lectures.

Work placements

Not applicable.

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 indices, to evaluate the characteristics of inventory management.

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

Attendance at lectures is not compulsory but is recommended.
Attendance at exercises is not compulsory but is recommended.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

KROPÁČ, J. Statistika A. 3. vyd. Brno : FP VUT, 2008. ISBN 978-80-214-3587-2.
KROPÁČ, J. Statistika B. 2. vyd. Brno : FP VUT, 2009. ISBN 978-80-214-3295-6.
KROPÁČ, J. Statistika C. 1. vyd. Brno : FP VUT, 2008. ISBN 978-80-214-3591-9.

Recommended reading

ČSN ISO 8258: Shewhartovy regulační diagramy. ČNI Praha, 1993.
TOŠENOVSKÝ, J., NOSKIEVIČOVÁ, D. Statistické metody pro zlepšování jakosti. Ostrava : Montanex a.s. ISBN 80-7225-040-X.
KROPÁČ, J. Statistika. 1. vyd. Brno : FP VUT, 2010. ISBN 978-80-214-3866-8.

eLearning

Classification of course in study plans

  • Programme MGR Master's

    branch MGR-ŘEP , 1. year of study, winter semester, compulsory
    branch MGR-UFRP-D , 2. year of study, winter semester, compulsory
    branch MGR-PFO , 2. year of study, winter semester, elective

Type of course unit

 

Lecture

13 hours, optionally

Teacher / Lecturer

Syllabus

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

Exercise

26 hours, compulsory

Teacher / Lecturer

eLearning