R for Social Scientists

By Angela Li, Ben Marwick, Christina Maimone, Danielle Quinn, Erin Alison Becker, Francois Michonneau, Geoffrey LaFlair, Hao Ye, Jake Kaupp, Juan Fung, Katrin Leinweber, Martin Olmos, Murray Cadzow.
Analysis Data Education Open Scholarship Tools and Technologies R Reproducibility Research Data Management Tools Researchers RStudio

Abstract

Data Carpentry lesson part of the Social Sciences curriculum. This lesson teaches how to analyse and visualise data used by social scientists. Data Carpentry’s aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain. The lessons below were designed for those interested in working with social sciences data in R. This is an introduction to R designed for participants with no programming experience. These lessons can be taught in a day (~ 6 hours). They start with some basic information about R syntax, the RStudio interface, and move through how to import CSV files, the structure of data frames, how to deal with factors, how to add/remove rows and columns, how to calculate summary statistics from a data frame, and a brief introduction to plotting.

Link to resource: https://datacarpentry.org/r-socialsci/

Type of resources: Module

Education level(s): Graduate / Professional

Primary user(s): student, teacher

Subject area(s): Information Science, Measurement and Data, Social Science

Language(s): English