• Piecemeal R
  • 1 Welcome
    • About
  • 2 Introduction
    • 2.1 Materials
    • 2.2 Crafts
    • 2.3 Arts
    • 2.4 More examples 1
    • 2.5 More examples 2
    • 2.6 Reflections
  • 3 Essentials
    • 3.1 Cheatsheets
    • 3.2 Data types
      • 3.2.1 Atomic
      • 3.2.2 Factor
      • 3.2.3 Matrix
      • 3.2.4 Data Frame
      • 3.2.5 List
    • 3.3 Programming
      • 3.3.1 Operator
      • 3.3.2 If else
      • 3.3.3 Loop
      • 3.3.4 Function
      • 3.3.5 Environment
      • 3.3.6 Debugging
      • 3.3.7 Stat func.
      • 3.3.8 String func.
      • 3.3.9 Set func.
    • 3.4 Housekeeping
      • 3.4.1 Working directory
      • 3.4.2 R session
      • 3.4.3 Save & load
      • 3.4.4 Input & Output
      • 3.4.5 Updating
  • 4 Piecemeal Topics
    • 4.1 Unusual Deaths in Mexico
      • Materials
      • Arts & Crafts
      • Exercise
      • The Key
      • Reflections
    • 4.2 Action, Romance, and Chicks
      • Materials
      • t-test
      • Bootstrapping
      • Linear Models
      • Exercise
      • The Key
      • Reflections
    • 4.3 Demo. Mixed Effects Models and LSMEANS
      • Mixed Effect Models
      • Visualizing Model Fit
  • 5 Resources
  • References
  • Published with bookdown

Piecemeal R

5 Resources

Here are more resources for learning R.

Free Books

  • Official CRAN R Manual

  • Quick R

  • The Art of R Programming by Norman Matloff

  • ModernDive

  • Impatient R

  • Simple R by John Verzani

  • Introduction to Probability and Statistics Using R By Jay Kerns

  • R Wikibook

  • Cookbook for R by Winston Chang

  • OnePageR

  • The R Inferno

Videos

  • Coursera’s four week course videos

  • Workflow example video by Jermey Chacon

  • Video on Youtube

Tutorials

  • Exploratory Data Analysis in R (Recommended)

  • R Tutorial

  • R Bootcamp - Jared Knowles

  • Step-by-step (sequential) interactive tutorial- Try R

  • Another step-by-step interactive tutorial - swirl

With Small Fees: Tutorials from DataCamp

  • Cleaning Data in R

  • Data Manipulation in R with dplyr

  • Data Visualization in R with ggvis

  • Data Visualization with ggplot2

Introduction to Coding

  • Coding Resources for Beginners by Tori Dykes

Introduction to Shiny

  • Excel Tools to Shiny (the author’s Shiny tutorial)