Another of my clients is about embark on another round of A/B testing, so I thought I’d post some of my favorite A/B testing resources, summarizing each as a single rule: Why you should always set your sample size (n) in advance: In How Not to Run an A/B Test @evmill makes the case for always fixing your sample size in advance. I generally agree with him – this is good research design.

I’ve been doing a lot of data analysis for a couple clients lately; I’m using R pretty heavily, and thought that I would create this post to keep track of the R resources I use most. This post will be updated frequently over the coming days as I fine-tune my R installation. Things I use or recommend: Stats Mini-Courses from the UCLA Statistics Center, including a lot of valuable information on the basics of loading and manipulating data in R Getting Started (on Mac):