R Analysis

This wiki is designed to help anyone perform statistical analyses on their data using R. It is divided into 3 broad sections: the first section outlines basics of how R deals with data using built in data sets, the second will help you to read in and organize your own data, and the third will help to summarize, run stats, and output graphs of your data.

Each section is organized into a series of questions. Start from the beginning if you are new to R, or click on a question to go to a detailed answer and/or examples.

To get started, download R for free from the R website

Part 1: R basics

• What is a data frame?
• Viewing the whole data frame?
• Viewing the head or tail of a data frame?
• Summary of data frame?
• Dimensions of your data frame?
• Viewing a single row or single column?
• Viewing multiple rows or multiple columns?
• Single variable of the data frame?
• Summary of single variable of the data frame?
• Commands on a single variable?
• Viewing the names of all variables in the data frame?
• Changing a variable name?
• Changing all variables names?
• Creating a new variable from scratch?
• Creating a new variable based on values of another variable?
• Viewing cases of an IV that meet certain conditions?
• Finding the indices of an IV that meet certain conditions (which)?
• Finding values of one variable that correspond to values of another variable that meet certain conditions?
• Different variable types/classes?
• Specifying Independent and Dependent variables?
• How to load a library/package?

Part 2: Organizing your data

This section describes how to load in data files into a data frame, add or drop columns, create a new data frame from a subset of the full data, and generally get your data into the form you need so you can then conduct your analyses.

how to read your data into R

• reading in a single delimited file
• reading in multiple-delimited files and storing into a main data frame
• reading in files and creating a subject variable/other variable based on the file names

how to fill out and complete your main data frame

• adding a new variable based on another variable (selecting string subset by static position)
• adding a new variable based on another variable (selecting string subset by regular expression)
• adding a new variable based on another variable (logical statement using exact matches)
• adding a new variable based on another variable (logical statement using static subset position)
• adding a new variable based on another variable (logical statement using regular expressions)

how to select a subset of your main data frame

• assigning a new data frame
• selecting columns from your main data frame
• selecting rows from your main data frame
• selecting columns and rows from your main data frame
• changing your RT variable into a validity effect variable (invalid RT - valid RT)

Part 3: Analyzing your data

This section outlines how to perform descriptive stats, inferential stats, and output graphs once your data frame is organized