Course detail

Applied Statistics

FP-asKAcad. year: 2020/2021

Random Variables, Methods of Mathematical Statistics, Pivot tables, Correlation Analysis, Multinomial Regression, 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 estimate parameters of regression model, to evaluate a survey, 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.

Prerequisites

Fundamentals of probability theory and mathematical statistics.

Theory of probability, random variables, random vectors.

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

Přibližný počet výsledků: 211 000 000 (0,40 s)
Čeština
Angličtina

exam
test at the end of the semester (first dates in December, then about 2 more dates in the exam period)
the test contains questions from theory as well as practical examples
to pass the exam you need to get at least 50% of the points from the test


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

In the case of distance testing, the exam will be solved during the semester, but it will take place similarly as if it were held in full-time form (test in electronic form + oral exam in theory via Microsoft Teams)

Course curriculum

Week 1: discrete and continuous random variables (binomial, geometric, hypergeometric, Poisson, alternative, negative binomial distribution, characteristics, probability distributions)
Week 2: continuous random variables (uniform, normal, normalized normal, exponential distribution, density, quantilles)
Week 3: confidence intervals and hypothesis testing (quantiles, construction of point estimates and their interpretation)
Week 4: processing of data files one-dimensional and two-dimensional (measures of location and scattering, mean, median and percentiles, variation range and variance, histogram, empirical distribution function)
Week 5: Pivot tables (general and 2x2 table, test of goodness of fit, pivot tables in Excel)
Week 6: regression analysis (simple and multiple regressiont)
Week 7: regression analysis (the quality of the regression model determination coefficient, t test and F-test)
Week 8: statistical process control measurements (three types of control charts, statistical control of the manufacturing process, identifiable cause)
Week 9: statistical process control comparisons (four basic types of control charts), Target Control Charts
Week 10: capability indices (upper and lower tolerance limit, target value, interpretation capability index)
Week 11: Inventory management (model dependent demand)
Week 12: Inventory management (independent demand model)
Week 13: Acceptance sampling (statistical acceptance inspection measurements and statistical comparisons)

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 in Excel, to estimate parameters of regression model in Excel and to interpret these parameters, to evaluate a survez in Excel, to use methods of statistical process control, process capability indices, to evaluate the characteristics of acceptance sampling and inventory management.

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

Attendance at lectures 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-KS Master's

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

Type of course unit

 

Guided consultation in combined form of studies

16 hours, optionally

Teacher / Lecturer

eLearning