To analyze data using appropriate statistical procedures;
To use suitable software tools to perform statistical calculations;
To plan correctly statistical studies in biomedical sciences;
To judiciously evaluate the results of studies published in the literature;

Introduction to exploratory data analysis: level of measurement, measures of location and dispersion.
Descriptive statistics and data visualization: numerical indicators and graphics. Databases: creation, labeling and debugging.
Probability: concept and algebra. Random variables and probability functions. Discrete probability distributions: binomial and Poisson. Continuous probability distributions: normal, normal standard and t-Student. Central limit theorem.
Inferential statistics. Sample, population and sampling techniques. The estimation theory: point estimation and confidence intervals.
Statistical hypothesis and hypothesis testing. Level of significance and power of a test. P value. Parametric and non-parametric tests.
Methods of regression and correlation;
Statistical methods of supervised and unsupervised classification.