Advanced Programming in R

Date:

14/12/2021 - 15/12/2021

Organised by:

Royal Statistical Society

Presenter:

Dr Colin Gillespie or Dr Jamie Owen

Level:

Advanced (specialised prior knowledge)

Contact:

training@rss.org.uk

video conference logo

Venue: Online

Description:

This is a two-day intensive course on advanced aspects of R programming. This workshop is primarily aimed at R users who do not have a formal background in computing. The course will be a mixture of lectures and computer practicals and will cover conditional programming structures, functional programming, S3 and S4 objects.

Delegates are expected to bring a laptop with the R software installed.
 

Learning Outcomes

  • An understanding of object orientated programming.
  • Appreciate the fundamental differences between the S3 and S4 object systems.
  • Be able to create S3, S4 and reference objects with associated methods.
  • An understanding of R environments and how they can be leveraged to form function closures.
  • An appreciation of when it is appropriate to use different object types.

 

Topics Covered

  • An overview of object orientated programming.
  • Anonymous functions.
  • Returning functions (closures).
  • Passing functions as arguments.
  • The R environment.
  • The S3 and S4 object structures.
  • Reference objects and mutable states.
  • Object methods and generic functions.

 

Target Audience

The course will be of interest to anyone who uses R, in particular those who want to develop their computer skills to cover more advanced topics. This course would be useful for participants who do not have a formal background in programming.
 

Delegate Feedback

“I am not scared of R anymore. It was actually fun!”

“The balance between lectures and practicals was good”

“Very clear lectures and hand-outs”

Cost:

£588 - £816 (inc. VAT)

Website and registration:

Region:

Greater London

Keywords:

Quantitative Data Handling and Data Analysis, R

Related publications and presentations:

Quantitative Data Handling and Data Analysis
R

Back to archive...