R is an expressive domain-specific programming language for describing statistical problems. For example, it’s easy to create vectors, apply functions to them, and filter them (shown here using the R interactive shell).

=> | x <- seq(1,10,.5) # x = 1, 1.5, 2, 2.5, 3, 3.5, ..., 10 |

=> | y <- 1:5 # y = 1, 2, 3, 4, 5 |

=> | z <- c(9,6,2,10,-4) # z = 9, 6, 2, 10, -4 |

=> | y + z # add two vectors |

<= | [1] 10 8 5 14 1 # result is 1-dimensional vector |

=> | z[z<5] # all elements in z < 5 |

<= | [1] 2 -4 |

=> | mean(z) # compute the mean of vector z |

<= | [1] 4.6 |

=> | zero <- function() { return(0) } |

=> | zero() |

<= | [1] 0 |

R is a medium-sized but complicated programming language, and most or all of us have a handicap: we don’t know R. That means we ...

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