Oliver Kirchkamp
[A picture of Oliver Kirchkamp]

Introduction to R

  • Introduction
  • Syntax
  • Control structures
  • Functions
  • Input and output of data
  • Graphs
  • Simple Regressions
For our practical examples (during the entire course) we will use the software environment R. I think that it is helpful to coordinate on one environment and R has the advantage of being free and rather powerful.
  • Documentation for R is provided via the built in help system but also through the R Homepage. Useful are
    • The R Guide, Jason Owen (Easy to read, explains R with the help of examples from basic statistics)
    • Simple R, John Verzani (Explains R with the help of examples from basic statistics)
    • Einführung in R, Günther Sawitzki (In German. Rather compact introduction.)
    • Econometrics in R, Grant V. Farnsworth (The introduction to R is rather compact and pragmatic.)
    • An Introduction to R, W. N. Venables und D. M. Smith (The focus is more on R as a programming language)
    • The R language definition (Concentrates only on R as a programming language.)
  • We will use the following packages: car, Ecdat, MASS (VR), UsingR, binom, relaimpo, lmtest, mvtnorm, lattice, clinfun, memisc, xtable. If, e.g., the command library(Ecdat) generates an error message (Error in library(Ecdat): There is no package called 'Ecdat'), you have to install the package.
    Installing packages with Microsoft Windows:
    Start Rgui.exe and install packages from the menu Packages / Install Packages).
    Installing packages from advanced operating systems:
    From within R use the command install.packages("Ecdat"), e.g., to install the package Ecdat
  • In the lecture we will use RStudio as a front end.