Jack Taylor | Visualising variability and uncertainty in R @RIOTScienceClub
Jack Taylor | Visualising variability and uncertainty in R  @RIOTScienceClub
Uploaded November 2020 | Updated September 2026, 1 week ago
About the speaker

Jack Taylor is a PhD student at the University of Glasgow. He is in interested in how we represent words, particularly how we represent and access concepts associated with words, like emotion and imageability. Jack is also interested in the extent to which we predict the visual features of words, given a semantic context. Jack also has a keen interest in supporting reproducible research practices, including data visualisation among others, and you can find some useful links below. Jack can also be found on Twitter @JackEdTaylor.



About the talk

A picture is worth a thousand words, and good data visualisation is worth a thousand summary statistics. I’ll argue that good data visualisation is a key component of open and transparent science. I’ll highlight some example ways of visualising data transparently, focusing on presenting individual observations, visualising uncertainty, and embracing variability. Because it’s well-known, I’ll show some implementations in the ggplot2 package of R, highlighting some really useful functions and extensions for presenting informative features of data and statistical models.

About RIOT Science Club

The RIOT Science Club gives talks/workshops on Reproducible, Interpretable, Open & Transparent Science.

Slides and/or recordings of all past and future RIOTS Clubs are stored on our Open Science Framework Page: osf.io/8y7h2/. You can also subscribe to our mailing list, to receive regular information on upcoming talks and workshops, any local events and vacancies for positions in open and reproducible research.

You can also find us on Twitter @riotscienceclub.

If you would like to give a talk or workshop for The RIOTS Club, please email riotscienceclub@kcl.ac.uk.
Jack Taylor | Visualising variability and uncertainty in ROpen & reproducible neuroimaging: from study inception to publication Dr Botvinik-Nezer & Dr NisoDr Jill Jacobson | Interpreting replicationsDr Peter Branney | Opportunities and challenges of open science for qualitative methodsDr Larissa Shamseer | False dichotomy: Predatory journals and inclusivity and scholarly publishingSimulating the destructive power of p-hacking - Angelika StefanOpen and reproducible research at CERN by Dr Sunje Dallmeier-TiessenDr Crystal Steltenpohl | Transparency in qualitative research and using Dedoose for codingTori Egherman | Communicating on the Efficacy of Facemasks: What Went WrongProf David Colquhoun | Why p-values cant tell you what you need to know and what to do about itUsing StatCheck: a four-step robustness check of your research - Michèle NuijtenDr Moin Syed | Stop talking about diversity in open science
RIOT Science Club |

Jack Taylor | Visualising variability and uncertainty in R

SHARE TO X SHARE TO REDDIT SHARE TO FACEBOOK WALLPAPER