Statistics

• Descriptive Statistics: Graphical representations, calculation of relevant measures of central tendency etc., also by using a computer; application of methods for large data sets, analysis and comparison of results, critical discussion and evaluation of methods and their use in scientific projects and business practice
• Probability theory: important laws, dependent probabilities, Bayes Rule; application to practical problems
• Use and application of probability distributions , as e.g. Binomial and Normal distribution to Management and Engineering problems
• Methods of inferential statistics: confidence intervals: theoretical background and applications; hypothesis testing: theoretical background and application to business problems; regression analysis: theoretical background and application in research practice.
  
  Operations Research

• Linear Programming: Modelling business decision situations, solving problems by Simplex method and by using software, theoretical background of Simplex procedure, Dual Simplex procedure and blocked variables, special cases (degeneracy etc.); sensitivity analysis and interpretation
  
• Transportation planning: Modellung transportation and transshipment problems in global networks; Solving transportation problems using software
• Network Optimization problems: modelling production and transportation networks, solving planning problems in networks, Network Planning as a research topic
  
• Integer Programming: Models using integer variables, e.g. in location decisions, branch and bound procedure