Computer science

Industrial Engineering & Management

Course description

This course covers the following areas of probability theory: axiomatic foundations, random variables, distributions, and densities; expectations; introduces both discrete and continuous families of distributions; multiple random variables: joint and marginal distributions, properties of random samples: convergence, sampling from normal distribution, Central Limit Theorem and all other relevant topics for the exam on Probability Theory.

Topics

**Experiment & Combinatorial Probability****Conditional probability & independence****Discrete random variables****Discrete variables & Continuous random variables****Continuous variables & Waiting times**

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