Statistical Analysis and Decision-making

The course is not on the list Without time-table
Code Completion Credits Range Language
51XESRA KZ 4 2P+1C Czech
Institute of Pedagogical and Psychological Studies

Student will be introduced into using of statistical methods by describing onedimensional and twodimensional populations (with regression and correlation analysis).

Student will be introduced into the probability theory, including basic distributions and statistical estimate and tests.

The subject can be applied in the following fields: models of linear programming, inventory, queuing, network, simulation.


Requirements for term work:

1.Work with sample (ca 120 data) and calculation of descriptive statistics (measuring of central tendency and measures of variance).

2.Example for regression and correlation analysis.

3.Approximation and arrangement of histogram with normal distribution.

4.Linear programming.

5.Methods CPM and PERT.

6.Models for decision analysis (models of inventory, queuing, investment, simulation).

Part of the classified assessment is the examination from the subject taught in courses.

Syllabus of lectures:


1.Statistical population and descriptive statistics (measures of central tendency).

2.Statistical population and descriptive statistics (measures of variance).

3.Regression and correlation analysis (linear and nonlinear).

4.Multiple regression and correlation analysis.

5.Basic probability distributions (discrete models).

6.Basic probability distributions (continuous models).

7.Application approximation and arrangements.

8.The arrangements of histogram with normal distribution.

9.Network analysis (CPM ? Critical Path Methods and Program Evaluation and Review Techniques).

10.Linear programming.

11.Inventory models and queuing models.

12.Models of investment policy.

13.Simulation models (Method Monte Carlo).

Syllabus of tutorials:

Curriculum for exercises:

1.Statistical population and descriptive statistic.

2.Regression and correlation analysis.

3.Basic probability distributions.

4.Approximations and arrangements statistical, estimates and tests.

5.Linear programming and network analysis.

6.Models of inventory, queuing, investment and simulation.

Study Objective:

Understand how to use statistical and decision analysis in enterprise problems and processes.

Study materials:

Kožíšek, J., Stieberová, B.: Statistická a rozhodovací analýza, VČVUT v Praze, 2008

Kožíšek, J.: Statistická analýza ? příklady, VČVUT v Praze, 2002

Gros, I.: Kvantitativní metody v manažerském rozhodování, Grada, Praha 2003

Further information:
No time-table has been prepared for this course
The course is a part of the following study plans:
Data valid to 2020-09-25
For updated information see http://bilakniha.cvut.cz/en/predmet2338906.html