- Calculate probabilities of random events, expected values, variances and covariances of random variables both analytically and with the Mathematica programme (k2,k3)
- Apply the stochastic processes as mathematical models of systems and phenomena that appear to vary in a random manner (k2,k3)
|
- Random experiment, relative frequency, Laplace experiments, combinatorial calculations, geometric probability, conditional probability, independent events, random variables and distributions
- Probability densities of discrete and continuous distributions, cumulative distribution functions, expectation and variance, joint distributions, conditional distribution, independent random variables, the binomial distribution, the Poisson distribution, the normal distribution
- Definition of a stochastic process, the Bernoulli process, the Poisson process, random Walk, Brownian motion, stationarity of stochastic processes
- Markov chain with a discrete time, Markov chain with a continuous time
|
