Course description: Statistics teaches us how to behave in the face of uncertainties — according to the famous mathematician, Abraham Wald and the book `Statistics and Truth’ of C.R. Rao. Theoretically, we will learn strategies of treating chances in everyday life, where our inference is based on a randomly selected sample from a large population, and hence, we intensively use concepts of probability (laws of large numbers, Bayes rule). Parameter estimation and hypothesis testing (parametric and non-parametric inference) are introduced on a theoretical basis, but applications are intensively discussed and presented on real-life data. Methods of supervised and unsupervised learning are outlined for multivariate data sets; former include regression and discriminant analysis, while latter include factor and cluster analysis. The students are made capable of solving real-world problems by choosing the most convenient method or statistical test. Outputs of the BMDP (biomedical program package) are also analyzed in the classes.