I like Absolver. I want to love it, but I can't. Not right now. It's core gameplay can be satisfying and thrilling, requiring deliberate, precise control to succeed. There is an impressive depth of strategy while still being approachable. But sometimes clunky controls, often buggy online play, and some obtuse mechanics and design choices have lead me to quit the game in frustration far too often at this point. The core combat mechanics are strong enough to keep me coming back for now, but I'm not sure how long that will last without some updates, particularly to the online experience.

I don't post on this site much and that bothers me. I want to write more, often have ideas for things to write about, and may even jot down some notes and thoughts, but rarely get around to posting things. Why? To be honest, I don't post here mostly because I'm kind of afraid to.

I have been developing the A/B testing procedure that I want to use in an upcoming experiment at work. Generally speaking I'm on team Bayes when it comes to statistical matters, and that's the approach that I will take in this case as well. In this (long) post I'll outline a method for Bayesian A/B testing that is largely built on some excellent blog posts by Evan Miller, Chris Stuccio, and David Robinson. In this post I'll summarize the results of Miller and Stuccio, ending up with a decision function for A/B testing based on the gain expected from making the change that is under consideration. I go a bit further than the referenced posts by deriving a measure of uncertainty in the expected gain that can be used to determine when a result is significant and overcome the "peeking" problem discussed in Robinson's post. Lastly I calculate the expected difference between the two procedures under test (as opposed to the gain which is the difference but only when the new procedure is better). Throughout I present some simulated examples to give a sense of the impact of the different parameters in the model and to illustrate some aspects of the model that one should be aware of.

The concept of closures is something that I've been familiar with for a while, but I haven't used in my own work until recently. I started thinking more about closures while reading A Software Engineer Learns HTML5, JavaScript and jQuery by Dane Cameron (an excellent book, btw). They are introduced …

I have recently started diving into Apache Spark for a project at work and ran into issues trying to process the contents of a collection of files in parallel, particularly when the files are stored on Amazon S3. In this post I describe my problem and how I got around …

I've been using IPython notebooks a lot lately for both my personal and professional research and analysis projects. It's a great tool for keeping code, visualization and analysis together in one place. It's also convenient for communicating results. Just export your notebook to HTML and it's ready to distribute... except …