- Description of data and observations.
• Events and sets. Probability theory. Conditional probability.
• Unidimensional discrete and continuous random variables. Probability and Density functions. Distribution function. Moments of random variables.
• Discrete Distribution laws: discrete - uniform, Bernoulli, binomial, geometric, hypergeometric, Poisson.
- Continuous Distribution Laws: uniform, normal, exponential, gamma, chi-square. Sums of random variables.
- Central Limit Theorem and its corollaries.
• Relation between different random variables: covariance and correlation. Bivariate joint distributions.