Teaching Materials

  1. Lessons
    • An introduction to the R environment explaining the most important data structures as vectors, matrices, arrays, data frames, lists and factors: pdf_icon_link (Italian).
    • How to write and run functions and scripts, how to control the execution flow and how to import/export data in R (a few of I/O functions): pdf_icon_link (Italian).
  2. Practise
    • Solutions to the exercises proposed in the first lesson: Sol_ex_lesson0.R;
    • R Implementation of several statistical functions like mean, median, mode, variance, percentile, frequency distribution, Gini Index, Shannon Entropy and much more in order to make an "homemade" statistics library: LibStat.R;
    • A real-world example: an application of Gini index (using the functions of the LibStat library): GinIndex.R;
    • R graphics: basic commands to create charts with R: Rplots.R;
    • Simulation of Discrete and Continuous Probabilities: Probabilistic_Models.R;