Emma Rand and Mine Çetinkaya-Rundel In September, we will be delivering a series of four online one-hour package development workshops. These are: Packages in a nutshell 20 September 2021 at 14:00 BST Register! Slides Setting up your system 21 September 2021 at 14:00 BST Register! Slides Your first package! 23 September 2021 at 14:00 BST… Continue reading R Forwards ?... [Read more...]

R Forwards is an R Foundation task force that was originally set up in December 2015 to address the underrepresentation of women in the R community. An analysis of CRAN package maintainers estimated that fewer than 15% were women, and a useR! participant survey found that women were less likely than men ... [Read more...]

Date: Tuesday, 7th January, 2020, 10:30-15:30 Location: University of York, UK Forwards is the R Foundation taskforce on women and other under-represented groups and we are offering a free workshop designed for people who use R coding and want to learn more about creating impact from their code. It will cover ... [Read more...]

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It’s a challenge for an experienced user to remember what it was like to be totally new to R and come up with explanations that don’t draw on understanding developed subsequently. Terminology with which you have become very familiar is, in fact, jargon. So I asked a novice, ... [Read more...]

RStudio makes R easier to use. It includes a code editor, debugging & visualization tools. I love it but when beginners launch RStudio they are sometimes confused by all the panes and tabs. Here I have tried to give a quick visual guide to the anatomy of RStudio for people new ... [Read more...]

Remember to reference R When people are new to using R and, perhaps, to referencing and report writing in general, they often don’t know they should cite and reference R and its packages. We do this for the same reasons we reference any thing else in any academic work. ... [Read more...]

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 … and non-normally distributed data can be normal One of the underlying assumptions of many statistical methods is that the data (or the model residuals) are normally distributed. I teach students to evaluate this assumption with plots and normality tests. When they find their data do not seem to be normally ... [Read more...]