Publications

Papers and articles

Published articles

Presenting data the Significance way - Part 1.
N. Rennie, A. Krause. Significance. Volume 21. Issue 3. July 2024. doi: doi.org/10.1093/jrssig/qmae045
Journal article

Outlier detection in network revenue management.
N. Rennie, C. Cleophas, A. M. Syksulski, F. Dost. OR Spectrum. Volume 46 (pages 445–511). 2024. doi: doi.org/10.1007/s00291-023-00714-2
Peer reviewed Journal article

Creating Christmas cards with R.
N. Rennie. Real World Data Science (online). 2023. Link: realworlddatascience.net/ideas/tutorials/posts/2023/12/12/xmas-cards.html
Online Blog

Best practices for data visualisation.
A. Krause, N. Rennie. B. Tarran. Royal Statistical Society (online). 2023. Link: royal-statistical-society.github.io/datavisguide
Online Guidelines

Analysing and visualising bike sharing demand with outliers.
N. Rennie, C. Cleophas, A. M. Syksulski, F. Dost. Discover Data. Volume 1, Issue 1. March 2023. doi: doi.org/10.1007/s44248-023-00001-z
Peer reviewed Journal article

We’re not getting any younger! Or should that be older?
N. Rennie. Significance (online). 2022. Link: significancemagazine.com/we-re-not-getting-any-younger-or-should-that-be-older
Online Blog

Identifying and responding to outlier demand in revenue management.
N. Rennie, C. Cleophas, A. M. Syksulski, F. Dost. European Journal of Operational Research. Volume 293, Issue 3, 16 September 2021, 1015-1030. doi: doi.org/10.1016/j.ejor.2021.01.002
Peer reviewed Journal article

Preprint articles

Prevalence of radiological cerebral small vessel disease: an insight from routinely collected data.
M. P. Maskery, N. Rennie, S. Mathur, J. Knight, H. C. A. Emsley. Preprint. November 2023. doi: doi.org/10.21203/rs.3.rs-3625684/v1
Preprint

PhD Thesis

Detecting demand outliers in transport systems.
N. Rennie. PhD Thesis. 2021. doi: doi.org/10.17635/lancaster/thesis/1448
PhD Thesis

Blog posts

Besides the blog posts you’ll find on this website, I’ve also contributed blog posts to a variety of other organisations:

Real World Data Science

Real World Data Science is a project from the Royal Statistical Society, in partnership with the American Statistical Association. It’s developed by data science practitioners and leaders with a single goal in mind: to help deliver high quality, ethical, and impactful data science projects.

View contributed blogs

• Creating Christmas cards with R

Jumping Rivers

Jumping Rivers write blog posts on topics related to R, Python, and all things data science. You can find the blog posts I contributed when I worked as a Data Scientist at Jumping Rivers listed below.

View contributed blogs

• Alt Text in R: Plots, Reports, and Shiny
• What is R7? A New OOP System for R
• I’m an R user: Quarto or R Markdown?
• Highlights from rstudio::conf(2022)
• Custom colour palettes for {ggplot2}
• Thinking about maps and ice cream

Posit

The Posit (formerly RStudio) blog covers topics including industry, open source, products and technology, training and education, and data science leadership. You can find my contributed blogs listed below.

View contributed blogs

• Translating Shiny Apps for International Audiences

Software

See nrennie.rbind.io/projects/r-packages for a list of R packages I have developed and published.