Czech

Not applicable.

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.

Fundamentals of probability theory and mathematical statistics.

Theory of probability, random variables, random vectors.

Not applicable.

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.

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)

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)

Not applicable.

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.

Attendance at lectures is not compulsory but is recommended.

Not applicable.

Not applicable.

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.

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