Introduction to statistics and statistical machine learning, Introduction to the statistical package IBM SPSS STATISTICS, Introduction to the R language, Introduction to the Python language, Descriptive analysis of quantitative data, Graphical representation of quantitative data, Graphical methods for testing normality, Normality tests, Statistical inference for a sample, Statistical inference for two samples, Statistical inference for two dependent samples, Statistical inference for k independent samples, Statistical inference for k dependent samples, Description of categorical variables and inference for proportions, Contingency tables for qualitative variables, Diagnostic tests and ROC curves, Correlation of quantitative variables, Introduction to linear regression, Introduction to logistic regression, Introduction to survival analysis, Introduction to Ridge Regression, Introduction to co-variance analysis, Reliability assessment of a questionnaire, Introduction to factor analysis, Introduction to discriminant analysis, Introduction to cluster analysis, Introduction to neural networks, Introduction to the Nearest Neighbor method, Introduction to partial least squares regression, Introduction to decision trees, Case studies, Statistical tables, Bibliography, Greek-English glossary, English-Greek glossary