Programming in R


13/09/2022 - 14/09/2022

Organised by:

Royal Statistical Society


Dr Colin Gillespie or Dr Jamie Owen


Intermediate (some prior knowledge)



View in Google Maps  (EC1Y 8LX)


12 Errol Street, London


Level: Intermediate (I)

This is an intensive course on programming principles in R. During the course participants will gain experience of writing their own functions and scripts for undertaking bespoke data analysis tasks in R. Consideration of memory allocation, code profiling and leveraging parallel computation will also be explored to guide participants in the principles of efficient R programming.

Learning Outcomes

By attending the course participants will gain experience in writing their own functions and scripts for data analysis in the R programming language. They will improve on their data manipulation skills. Further, attendees will also gain an understanding of how to make code more efficient and to extend their workflow to leverage the power of parallel computing.

Topics Covered

  • Data manipulation and aggregation using dplyr
  • Control flow: conditional expressions, functional composition, for loops
  • The 'apply' family of functions
  • Efficient data structures
  • Code Profiling
  • Avoiding loops
  • Parallel computing


Target Audience

This course is idea for anyone who would like to extend their basic familiarity with using R, and using R to write their own bespoke functions or optimizing their code.

Assumed Knowledge

Basic prior experience with the R programming language is assumed. Namely that participants have some experience of R data structures, such as vectors, data frames, and experience in using pre-made functions from R packages.

The course is aimed as a follow up the 'Introduction to R and Regression Modelling in R' training course.
Whilst no statistical knowledge will be assumed, some of the examples will be statistical in nature.


£599.76 to £832.32 (including VAT)

Website and registration:


Greater London


Quantitative Data Handling and Data Analysis, R, Data manipulation , Dplyr , Control flow , Code profiling

Related publications and presentations:

Quantitative Data Handling and Data Analysis

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