How Premier League Elo scores can be used to predict the outcome of fixtures, using classification models in Sklearn


This article discusses how Bayesian estimation can be implemented in your digital experimentation methodology, with a specific focus on computation for continuous, non-discrete metrics

Figure created by Author (Frank Hopkins, 2020)

Introduction to CUPED

This article discusses how the Experimentation team have been accounting for pre-experiment variance in order to increase the statistical power of their experiments


This article will show how dot plots can be used to translate your experimentation findings in a digestible and jargon-free manner

Simple techniques that can be used to recommend anime content based on user-rating correlations and feature variables

Photo by Matt Popovich on Unsplash

How ODI Elo scores can be used to predict the outcome of fixtures, using machine learning and hyperparameter optimisation techniques in sklearn

Photo by Charlie Solorzano on Unsplash


This article explores prediction of user ratings scores using a number of feature variables in the MyAnimeList database

The BBC Experimentation and Optimisation Team discuss the scripting tools they have developed to assist products throughout the experimentation timeline

Using the Spotify API in R to visualise the most loved music of our friends and families


Frank Hopkins

Experimentation Data Scientist, specialising in digital experimentation. Posts ranging from data science to website optimisation and digi-analytics.

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