1. Introduction. Review of statistics. Programming languages. R language and RStudio. Basic commands.

  2. R syntax. Types of variables and objects. Functions. Operators. Vectors, factors, data.frames, lists. Functions and arguments in R. RStudio environment. R packages.

  3. Reading and writing data: Text and binary files. Reading daros with different packages. Encoding. Importing and exporting files from other applications. Connections. Reading data from the Internet.

  4. Tidy data and management of data. Split-apply-combine strategy for handling data. Pipes. Reordering of instructions from data.     

  5. Descriptive statistics. Calculation of descriptive statistics with R.

  6. Graphics. Principles of Tufte's Economics . Exploratory and expository graphs. Charts with R base: main chart types and options. Adding objects to a graph. Graph annotations. Composing several graphs. Exporting graphs.

  7. Package ggplot2. Grammar of graphs. Multivariate representation through aesthetic qualities of the graph. Geometries. Scales. Panels. Topics.   

  8. Programming with R. Ramifications. Conditions. Loops: logical conditions, functions.

  9. Inference. Point and interval estimation. The concept of confidence interval. Parametric and non-parametric hypothesis tests for different statistics. Concept of p-value. Quantile-quantile plots to examine normality. Contingency table.

  10. Regression and correlation. Simple linear regression. Quadratic regression. Transformation of potential and exponential relationships to linear. Residuals and diagnostics of a model. Confidence and prediction bands. Linear regression with several variables.

  11. One-way and two-way Anova. Diagnostics. Kruskal-Wallis and Friedman test. Interaction. Introduction to design.

  12. Power and sample size. The pwr package. Concepts of design experimental: confounding variables.

  13. Multiple and logistic regression. Model selection, stepwise procedures.

  14. Generalised linear models.

  15. Resampling methods. Bootstrap and permutations. Power calculation with simulations.

  16. Advanced topics. Sensitivity, specificity and ROC curves. Calculation of AUC and equivalence with Wilcoxon test. Introduction to survival analysis.