• HLPMiniCourseSession0

Session 0: Basics (with optional R primer)

11:00, May 27 2008

Understanding of this material will be assumed throughout the course. Please read these introductory materials and make sure you understand them before beginning the readings for the first session.

This optional meeting of the course will be an R primer. We'll be focusing on obtaining a basic level of familiarity required to participate in the course. We won't cover everything you'll need to know for the course, but hopefully we'll cover enough that you will be able to learn new material on your own.

If there are things you would like to cover, please make note of them below. NB: as of now there are no plans to teach graphing functions during the primer. It's possible that we could have a special add-on session to discuss different graphics packages in R if there's sufficient interest. Let AustinFrank know if you want to participate in such an event.

Reading

Assignments

• Make sure you have the latest version of R (version 2.7) installed on a laptop that you can use during class.

Topics

Interacting with R and R files

• Using a command line
  • command history, continuation lines, stopping execution defining variables calling functions
• Installing packages

  • install.package(), update.package()

• Using the R workspace

  • ls(), rm(), setwd(), getwd(), library()

• Using an R script file
• Saving R objects

  • save(), save.image()

Getting help

• Function-specific help

  • ?(), help()

• Searching the help

  • apropos(), help.search(), RSiteSearch()

Loading data

• general purpose functions

  • scan()

• specific formats

  • read.csv(), read.delim(), library(foreign)

General data structures

• vectors / arrays

  • c()

• matrices

  • cbind(), rbind(), table()

• lists

  • list(), unlist()

• data frames

  • data.frame()

• general structure manipulation and interaction

  • [], [[]], $, subset(), str(), cut(), repr()

Basic descriptive statistics

• summary stats

  • mean(), sd(), var(), quantile()

Probability distributions

• random sampling

  • runif(), rnorm(), rbinom()