These notes refer mainly to the examples and illustrations proposed in the book A Guide to<br/>Modern Econometrics by Marno Verbeek (4th and 3rd editions).<br/>The source codes here described are written in the R language (R Development Core Team<br/>2016) (R version 3.2.4 was used).<br/>Subjects were initially presented in the course Computational Laboratory for Economics<br/>held at Universit`a Cattolica del Sacro Cuore, Graduate Program Economics. The course ran<br/>in parallel with the course Empirical Economics where the methodological background were<br/>assessed.<br/>Attention is paid in order to obtain results first according to their mathematical structure,<br/>and then by using appropriate built-in R functions, always aiming at achieving an efficient<br/>and elegant programming style.<br/>The reader is assumed to possess the basic knowledge of R.<br/>In Chapter 1 some simulation results on the distribution properties of the sample mean are<br/>shown. Chapters from 2 to 10 reproduce results of examples and illustrations of Verbeek’s<br/>Guide. Appendix A1 describes how to read data from text, Stata, EViews and Microsoft<br/>Excel files. Appendix B contains results for examples which were present on the 3rd edition<br/>of Verbeek’s Guide.<br/>Detailed methodological presentations are given on the geometric interpretation of the<br/>linear model and OLS, on multicollinearity problems and their detection, on the assessment<br/>of distributional hypotheses (Chapter 2), on the interpretation of coefficients in linear<br/>regression model with logarithmic transformation of the outcome or of explanatory variables<br/>(Chapter 3), on the application of the GMM (Chapter 5), on the interpretation of marginal<br/>effects for logit and probit models and of odds ratio for logit models (Chapter 7) and on the<br/>classical presentation of stochastic processes (Chapter 8).<br/>Some companion material to these Lecture Notes can be downloaded from the booksite<br/>www.educatt.it/libri/materiali.<br/>I warmly thank Diego Zappa and Giuseppe Boari for having read parts of the manuscript.<br/>I wish to thank Stefano Iacus for his short course on an efficient and advanced use of R,<br/>and Achim Zeileis, Giovanni Millo and Yves Croissant for having improved their packages<br/>lmtest and plm in order to properly fit some problems here presented.