Introduction to R (Series 1)

Beginners

This module is part of the Social Science Research Methods Centre training programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

This workshop introduces students to one of the most frequently used statistics packages for social sciences, R. Students will learn how to download and install R, enter simple data into R, how to load data sets from other statistical packages into R, how to use the R environment for simple calculations, elementary graphs and tables. The module will introduce the use of code for performing these operations. This module is intended primarily for students who have not previously used R and who also do not have much previous experience with statistics. This is not a statistical methods course.

This module is intended primarily for students who have not previously used R and who also do not have much previous experience with statistics. This is not a statistical methods course.

• You must have a University Information Services (Computing) Desktop Services password (http://www.ucs.cam.ac.uk/linkpages/newcomers)
• You must have access to CamTools

Number of sessions: 4

• Session One (Why use R?; Downloading & installing R and R Studio; R interface – Using RStudio; Basics of R syntax: Objects in R - assigning values to variables, Basic mathematical operations, logical operators, Installing & loading packages)
• Session Two (Data handling: Uploading datasets; Creating & recoding variables; Recasting data)
• Session Three (Functions in R; Data types – vectors, matrices, lists, tables, dataframes; Conditional (IF) statements; For & while loops)
• Session Four (Descriptive stats; Graphics in R)

Students will learn how to download and install R, enter simple data into R, how to load data sets from other statistical packages into R, how to use the R environment for simple calculations, elementary graphs and tables.

Presentation, demonstration and practicals

• To gain maximum benefits from the course it is important that students do not see this course in isolation from the other MPhil courses or research training they are taking.
• Responsibility lies with each student to consider the potential for their own research using methods common in fields of the social sciences that may seem remote. Ideally this task will be facilitated by integration of the SSRMC with discipline-specific courses in their departments and through reading and discussion.

Four sessions of two hours each.

Once a week for four weeks.