- 27 September 2019: Kamaryn Tanner talked about machine learning in R using Super Learner — her materials are here.
- 26 July 2019: Sam Clifford talked about ggplot2 — one of the most popular packages in R, but also one of the least accessible without some introduction. His materials are here.
- 28 June 2019: Jenny Thompson and Amy Mulick explained how to do parallel processing in R using two alternative methods, based on the package parallel (material available here) and foreach/doParallel (material available here), respectively. Carl Pearson provided some additional info on parallelization within the LSHTM HPC system (here) and parallelization through data table (here).
- 30 May 2019: Rosalind Eggo and Hunter Blanks introduced us to the wonderful world of Git — materials available here, and Hunter’s nice hand-drawn diagrams here.
- 26 April 2019: Carl Pearson presented on data.table and make files. His presentation slides are here, and the .R files created during the session here.
- 4 April 2019: Hannah Brindle and Hope Simpson presented on using spatial data in R. The materials from Hope’s presentation are here (Hannah’s are awaiting approval from collaborators).
- 01 March 2019:Leonard Roth presented on using the package Rcpp as an alternative to using loops in R, which are known to be slow. Moving-on from using loops is a difficult but necessary step for those transitioning from Stata to R. The extensive materials from the session can be found here: Rcpp
- 31 January 2019: Missing Data: Matteo Quartangno presented on missing data in R — NA, NULL, NaN; what do they mean, and how do we deal with them? You can find the presentation slides and .R scripts here: NA NaN NULL R script.R Of NA, NaN, NULL & friends
- 29 November 2018: High Performance Cluster: Peninah Murage talked about how to use the high performance cluster available at the school. Her slides can be downloaded from here.
- 25 October 2018: Regression in R:Antonio Gasparrini presented on regression in R, getting us thinking again about the bread-and-butter of statistical research with R. The R code used during the seminar can be downloaded from here.
- 27 September 2018: Shiny Apps in R: Liz Fearon and Nick Magill shared their experiences of producing Shiny Apps in R. Here you can download the materias (slides and R code) used for the talk.
- 20 July 2018: Reproducible Research in R: Claudio Fronterre gave a presentation on Reproducible Research in R, followed by discussion. Comprehensive notes and a tutorial here.
- 28 June 2018: The Tidyverse: Chris Jarvis gave a presentation on the Tidyverse, covering dplyr and piping. Everything that he presented is available here.