Probability Theory - Period 1+2

The mathematical foundation for both modeling decisions under uncertainty when performing statistics is probability theory and probability theory therefore has a central role in the bachelor Econometrics and Operations Research.
The structure of this course is as follows.
- Basic elements of the probability account (random experiment, outcomes space, eventuality and opportunity) and fundamental calculation rules for opportunities on eventualities. Combinatorial probability models, conditional probabilities, the rule of Bayes, and the law of total probability.
- Introduction of the concept of a stochastic variable, and concepts such as distribution function, probability function, expectation and variance of a stochastic variable.
- Specific discrete probability distributions, such as the binomial, hypergeometric, Poisson, and geometric distribution.
- Continuous stochastic variables and associated probability distributions. Specific continuous probability distributions such as the uniform, normal, exponential and gamma distribution. Relations between these continuous probability distributions and the previously introduced discrete probability distributions are discussed.
- If there is sufficient time at the end of the course, the concepts of bivariate and multivariate probability distribution included related concepts such as joint and marginal distribution functions, conditional probability distribution and independence of stochastic variables.

Contact hours listed under a course description may vary due to the combination of lecture-based and independent work required for each course therefore, CEA's recommended credits are based on the ECTS credits assigned by VU Amsterdam. 1 ECTS equals 28 contact hours assigned by VU Amsterdam.