Blog Posts by Andrew B. Collier / @datawookie

Some instructions for installing Neo4j on Ubuntu 16.04. More for my own benefit than anything else.

In a previous post I detailed the process of compiling data on subject keywords used in articles published in PLOS journals. In this instalment I’ll be using those data to mine Association Rules with the arules package.

Uber exposes an extensive API for interacting with their service. ubeR is a R package for working with that API which Arthur Wu and I put together during a Hackathon at iXperience.

I’m putting together a couple of articles on Collaborative Filtering and Association Rules. Naturally, the first step is finding suitable data for illustrative purposes.

In previous instalments in this series I have not taken into account how odds can change over time.

I finally got tired of booting up Windows to download data from my Garmin 910XT. I tried to get my old Ubuntu 15.04 system to recognise my ANT stick but failed. Now that I have a stable Ubuntu 16.04 system the time seems ripe.

In the first instalment of this series we gained an understanding of the various types of odds used in Sportsbook betting and the link between those odds and implied probabilities. We noted that the implied probabilities for all possible outcomes in an event may sum to more than 100%. At first sight these seems a bit odd. It certainly appears to violate the basic principles of statistics. However, this anomaly is the mechanism by which bookmakers assure their profits. A similar principle applies in a casino.

I’m working on a project in which I need to systematically parse a number of RSS and Atom feeds from within R. I was somewhat surprised to find that no package currently exists on CRAN to handle this task. This presented the opportunity for a bit of DIY.

You can find the fruits of my morning’s labour here.

A couple of my collaborators have had trouble using read_html() from the xml2 package to access this Wikipedia page.

99% of my learning in the last decade has happened online, so this resonates with me.

This series of articles was written as support material for Statistics exercises in a course that I’m teaching for iXperience. In the series I’ll be using illustrative examples for wagering on a variety of Sportsbook events including Horse Racing, Rugby and Tennis. The same principles can be applied across essentially all betting markets.

Arthur Benjamin thinks that the end goal of teaching Mathematics at school should be Statistics rather than Calculus. He has a point: in terms of understanding things in the real world, Statistics is definitely more powerful. These ideas are quite compatible with those of Conrad Wolfram, who thinks that we should be using computers more extensively in Mathematics education.

Conrad Wolfram gives a thought provoking talk on a different way to teach Mathematics in schools.

Taking another look at the data from the lifespan package. Plot below shows the evolution of mortality in the US as a function of year and age.

I was rather inspired by this plot on Wikipedia’s List of Countries by Life Expectancy.

Working further with the mortality data from https://www.cdc.gov/, I’ve added a breakdown of deaths by age and gender to the lifespan package on GitHub.