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• Introduction and preliminaries
  Making R more friendly, R and available GUIs
  Rstudio
  Related software and documentation
  R and statistics
  Using R interactively
  An introductory session
  Getting help with functions and features
  R commands, case sensitivity, etc.
  Recall and correction of previous commands
  Executing commands from or diverting output to a file
  Data permanency and removing objects
  Simple manipulations; numbers and vectors
  Vectors and assignment
  Vector arithmetic
  Generating regular sequences
  Logical vectors
  Missing values
  Character vectors
  Index vectors; selecting and modifying subsets of a data set
  Other types of objects
  Objects, their modes and attributes
  Intrinsic attributes: mode and length
  Changing the length of an object
  Getting and setting attributes
  The class of an object
  Arrays and matrices
  Arrays
  Array indexing. Subsections of an array
  Index matrices
  The array() function
  The outer product of two arrays
  Generalized transpose of an array
  Matrix facilities
  Matrix multiplication
  Linear equations and inversion
  Eigenvalues and eigenvectors
  Singular value decomposition and determinants
  Least squares fitting and the QR decomposition
  Forming partitioned matrices, cbind() and rbind()
  The concatenation function, (), with arrays
  Frequency tables from factors
  Lists and data frames
  Lists
  Constructing and modifying lists
  Concatenating lists
  Data frames
  Making data frames
  attach() and detach()
  Working with data frames
  Attaching arbitrary lists
  Managing the search path
  Data manipulation
  Selecting, subsetting observations and variables
  Filtering, grouping
  Recoding, transformations
  Aggregation, combining data sets
  Character manipulation, stringr package
  Reading data
  Txt files
  CSV files
  XLS, XLSX files
  SPSS, SAS, Stata,… and other formats data
  Exporting data to txt, csv and other formats
  Accessing data from databases using SQL language
  Probability distributions
  R as a set of statistical tables
  Examining the distribution of a set of data
  One- and two-sample tests
  Grouping, loops and conditional execution
  Grouped expressions
  Control statements
  Conditional execution: if statements
  Repetitive execution: for loops, repeat and while
  Writing your own functions
  Simple examples
  Defining new binary operators
  Named arguments and defaults
  The '...' argument
  Assignments within functions
  More advanced examples
  Efficiency factors in block designs
  Dropping all names in a printed array
  Recursive numerical integration
  Scope
  Customizing the environment
  Classes, generic functions and object orientation
  Graphical procedures
  High-level plotting commands
  The plot() function
  Displaying multivariate data
  Display graphics
  Arguments to high-level plotting functions
  Basic visualisation graphs
  Multivariate relations with lattice and ggplot package
  Using graphics parameters
  Graphics parameters list
  Time series Forecasting
  Seasonal adjustment
  Moving average
  Exponential smoothing
  Extrapolation
  Linear prediction
  Trend estimation
  Stationarity and ARIMA modelling
  Econometric methods (casual methods)
  Regression analysis
  Multiple linear regression
  Multiple non-linear regression
  Regression validation
  Forecasting from regression