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This Software Carpentry workshop will introduce novice programmers to the R software environment, a powerful, popular and free statistical and graphical programming language. R is commonly used in many scientific disciplines for statistical analysis and its array of third-party packages. The emphasis of this workshop is to give attendees a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation.

Note that this workshop will focus on teaching the fundamentals of the programming language R, and will not teach statistical analysis.

Recommended Participants

Researchers looking for more advanced or automated data analysis capabilities than basic spreadsheets. The workshop is relevant for all disciplines. While it is designed to be suitable for people with no previous experience with R or other programming languages, participants do need to be confident and experienced with using computers, and a familiarity with command-line interfaces will be helpful.

Learning Objectives

  • Upload and process data in R to generate plots, figures and tables
  • Create and run functions in R
  • Write your own R script for automated data processing
  • Create automated reproducible reports in R
  • Install and load external R packages and manage R projects

Syllabus

The workshop will use the training material at swcarpentry.github.io/r-novice-gapminder/. Topics covered will include:

  • The Rstudio integrated development environment
  • The format of the R language – variables, data structures and functions
  • The import, export and processing of data within R
  • Generating high-quality graphic presentations of data
  • Building dynamic reports for reproducible research

Upcoming workshops

Introduction to Programming: R for Reproducible Scientific Analysis

27 September to 30 September, 9:00 am to 12:30 pm

Online

Introduction to Programming: R for Reproducible Scientific Analysis

21 November to 24 November, 9:00 am to 12:30 pm

Online