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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