This class will provide students with private tutoring tailored to the needs of their BSc./MSc. classes, enriched with additional educational material and personalized explanations based on the scope and level of their course. The tutorials may cover statistical/econometric material for analyses pertaining to the disciplines of psychology, economics, policy evaluation, management, political science, sociology and more. This class may cover any of the following topics: - Hypothesis Testing, Analysis of Experimental Data, Power, Effect Size - Parametric Inference and Estimation (i.e., regression, t-test, chi-square test) - Causal Inference with Observational Data (i.e., instrumental variables, difference-in-differences, regression discontinuity) - Probability Theory (i.e., LLN, CLT, probability distributions, Bayes theorem) - Non - parametric and Machine Learning methods (i.e., supervised classification/regression techniques, unsupervised/clustering techniques) - Coding in R, Python and SPSS - Quantitative methodology and evaluation of analysis results

This class will provide students with personalised, end-to-end guidance/supervision in empirical research projects. This could entail BSc./MSc. theses, academic projects/assignments or industry related work. These classes will provide hollistic support in all aspects of the empirical project, from data understanding, analysis, careful interpretation of the results and presentation through captivating and coherent storytelling. The class can also provide support with code implementation in R/Python/SPSS.