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ODSC Workshop: Intro to R

Paul Paczuski [AMA!]

Quick Start

This is a hands-on introduction to R. We will go through actual code and learn about data manipulation, graphics, and fundamentals of statistical modeling.

Set-up/Installation instructions are below.

A sample directory structure is in /templates

Contents

  • Set-up
  • Installing the R environment
  • Outline/Programs
  • Resources
  • Credits

Set-up

  1. Install R, RStudio, and the dplyr and ggplot2 packages [see Installing the R environment below]

  2. Download this repository ("Download Zip" link on the top right of this page) and unzip it to a convenient location on your computer. We will be working with its contents.

  3. Open R Studio

  4. Set the working directory to the /programs directory of the just-downloaded repository, as follows:

    • Session -> Set Working Directory -> Choose Directory...

    • Navigate and Open the /programs directory

  5. Open the file 0-intro.R [File - Open file...]. You will find it in /programs

Installing the R environment

Below are instructions to install R, a few packages, as well as RStudio, which we will be using during the workshop.

  1. Install R

    Mac OS X
    download and install from:
    http://cran.r-project.org/bin/macosx/ [click R-3.2.0.pkg on left]

    Windows
    download and install from:
    http://cran.r-project.org/bin/windows/base/

    Linux, etc
    See top of:
    http://cran.us.r-project.org

  2. Install the following R packages (see instructions which follow):

    ggplot2

    dplyr

    a) MAC OS X and Linux:

    • Open R (not RStudio for this step)
    • In Menu, go to “Packages and Data” - > “Package Installer”
    • Search for and install the above two packages (may need to choose a “mirror” - click on something in the USA) as follows:
    • Type in the name of one package, click “get list”, check “Install Dependencies” and then “Install Selected”
    • Do the same for the other package

    b) Windows:

    • Open R (not RStudio for this step)
    • In Menu, go to "Packages" -> "Install package(s)..." and select each of the packages at top to install.

  3. Install RStudio (a great interface for using R)

    Install for your appropriate system from the list at: http://www.rstudio.com/products/rstudio/download/

Outline/Programs

There are four R files in /programs. They will function as an "interactive notebook" for this workshop. Details follow.

  • 0-intro.R

  • 1-data.R

  • 2-graphics.R

  • 3-stats.R

0-intro.R

This will be a hands-on Introduction to R

  • "R is a free software environment for statistical computing and graphics"
  • "The best way to learn a new language is to try out the commands"

3 topics covered:

  1. data manipulation, including package dplyr
  2. graphics, including package ggplot2
  3. basic statistical models: linear and logistic regression

Go through code in the program

References:

  • James et al, p 42+ [see Resources section below]

1-data.R

Introduction to data manipulation

  • using base R functions

  • using intuitive, fast methods from dplyr

References:

2-graphics.R

Hands-on introductions to creating graphics in R

  • using base R methods

  • using the very popular ggplot2 package

References:

3-stats.R

We use statistical analysis for:

  • inference - making conclusions based on data

  • prediction - what will happen when I observe new data?

...and we create models to do both of those things.

"All models are wrong - some are useful."

Fundamentals:

  • model selection - which model is good/best?

  • model diagnostics/validation - is my current model reasonable and does it work?

  • uncertainty is always part of the final product

References:

  • James et al, p 15 [statistical modeling]

  • James et al, p 59+ [Linear regression]

  • James et al, p 130+ [Logistic regression]

Resources

Data Wrangling handout
http://www.rstudio.com/wp-content/uploads/2015/02/data-wrangling-cheatsheet.pdf

Quick-R
http://www.statmethods.net

An Introduction to Statistical Learning with Applications in R, by James et al:
http://www-bcf.usc.edu/~gareth/ISL/

Credits

Matthew Eaton for help with some workshop content
Hadley Wickham: dplyr, ggplot2, etc etc
ISLR book authors