Sample events and spaces. Independence, conditional probabilities and product spaces. Random variable. Discrete random variables (Bernoulli, binomial, Poisson, geometric and hypergeometric) and continuous (uniform, exponential, gamma, normal). Hope and variance. Covariance and correlation. Poisson process. Conditional probability, conditional expectation. Sequences of random variables: notion, concepts of convergence. Laws of Great Numbers: concept, the weak law, the strong law; applications. Central Limit Theory - situation of the problem; Central Limit Theorem; applications. Sample distributions (t, chi-square and F). Introduction to Statistical Inference.
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