Data organization e description, mean, median, mode, histograms, variance and standard deviation.

Normal model and correlation.

Sample space and events, probability axioms, binomial coefficient, conditional probability, Bayes' formula, independent events.

(approx. 6 hours)

Continuous and discrete random variables, probability density and cumulative functions, joint, conditional and marginal distributions, expected value, covariance, moment generating function. Random variables functions and transformations.

Random variable models: Bernoulli, Poisson, hypergeometric, binomial, uniform, normal, exponential, gamma, chi-square, t, F.

(approx. 24 hours)

Sample mean, central limit theorem, sample variance.

Maximum likelihood estimators, confidence intervals, bayesian estimators.

(approx. 18 hours)