Applied Mathematics

Course Code:
11APML
Academic Degree:
doctoral
Study Programme:
Logistics (P 3713)
languagestudy field / specialization
czech, englishL Transportation Logistics - 3706V006
Form of Study:
full-time and part-time
Type of Course:
obligatory
Course Completion:
exam
Course Supervisor:
doc. Ing. Ivan Nagy, CSc.
Supervising Department:
Department of Applied Mathematics (16111)
Abstract:
Descriptive statistics. Probability, conditional probability, Bayes theorem. Random variable, random vector, joint and marginal probability distribution, independence. Some discrete and continuous distributions. Mixed distributions. Finite mixture of distributions. Point estimation. Interval estimation. Hypothesis testing. Regression and correlation analysis. Simple graphs, multigraphs, labeled graph, planar graph, Euler´s formula. Four-color problem. Euler Circuit, Hamilton circuit and directed graphs. Algorithms for finding distances in digraphs - Dijkstra´s algorithm. Weighted graphs, shortest paths and minimal spanning trees. A depth first spanning tree, a breadth first spanning tree. Adjacency matrices. Flows in networks, Ford-Fulkerson´s algorithm.