
 Describe and apply basic concepts of probability theory such as outcome, event, probability, conditional probability, independence, stochastic variable, distribution, distribution function, frequency function, density, expectation, moment, (co)variance, correlation coefficient and moment generating function.
 Adequately model chance events.
 Describe and use the most important discrete and continuous distributions and their properties.
 Describe and apply moment generating functions, the Markov and Chebyshev inequalities, the weak and strong laws of large numbers and the central limit theorem.
 Use the technique of conditioning for the computation of probabilities and expectations.

 

 Assumed previous knowledgeBasic Calculus skills, including Double integrals, Geometric series, Taylor series. 
Bachelor Applied Mathematics 
  Required materialsBookS.M. Ross, Introduction to probability models, 9th International Student Edition, ISBN 9780123736352 

 Recommended materialsInstructional modesLecture
 PracticalPresence duty   Yes 
 Tutorial

 TestsProbability Theory


 