Simpson's Paradox backwards
I have been enjoying reading Judea Pearl’s new book Causal Inference in Statistics: A primer1
Pearl J. Causal Inference in Statistics. John Wiley & Sons; 2016 ↩
R functions you should know
A running list of R functions that I should have known, and didn’t with a minimal worked example in the style of tl;dr.
Parsing command line options in R
Notes to myself in the form of an R script about how to parse command line arguments. See StackOverflow for alternatives.
Get up, git up
I have been using SourceTree as a GUI for git, but just came across GitUp. It starts off just looking like a pretty way to view your repository with a fairly typical graph, but you can in fact work from within the graph.
A curated list of awesome R frameworks, packages and software.
Globally set options in R markdown
Normally you specify options in R markdown at the start of each chunk which requires typing them out for every block if they differ from the defaults.
Getting data into R
Science isn't broken
The important lesson here is that a single analysis is not sufficient to find a definitive answer. Every result is a temporary truth, one that’s subject to change when someone else comes along to build, test and analyze anew.
A day in the life ... visualised Data Analysis Using Regression and Multilevel/Hierarchical Models
These are notes from reading Andrew Gelman’s and Jennifer Hill’s 2007 edition of Data Analysis Using Regression and Multilevel/Hierarchical Models. I started reading this book a few days ago, so these are running notes which I will update as progress. You could consider this a live ‘book review’.