Statistical analysis is a good basis for a creation of decision-making models. The goal of this subject is to teach students to apply the selected statistical method, to apply models of decision analysis, to create models for the management of industrial enterprises.

1. Descriptive statistics and basic probability distributions
2. Statistical estimation and testing of statistical hypothesis (parametrical, nonparametrical tests)
3. Regression and correlation analysis
4. Cluster analysis
5. Discrimination analysis
6. Decision trees and neural networks
7. Inventory, Queuing and Network analysis models
8. Simulation models in the decision making
9. Mathematical programming
10. Data envelopment analysis
11. Multi-criteria decision making
12. Theory of games
13. Final exam

1. Descriptive statistics and basic probability distributions
2. Statistical estimation and testing of statistical hypothesis (parametrical, nonparametrical tests)
3. Regression and correlation analysis
4. Cluster analysis
5. Discrimination analysis
6. Decision trees and neural networks
7. Inventory, Queuing and Network analysis models
8. Simulation models in the decision making
9. Mathematical programming
10. Data envelopment analysis
11. Multi-criteria decision making
12. Theory of games
13. Final exam

Walpole, R.E., Myers, H.R., Myers, S.L.,Keing, Y.: Probability & Statistics for Engineers &; Scientists, Eight edition, Pearson Prentice Hall, 2007.
Devore, J. L.:Probability and statistics for engineering and the sciences, 5th ed., Pacific Grove : Duxbury, 2000.
Kottemann, K.: Illuminating Statistical Analysis Using Scenarios and Simulations, Wiley, 2017