Efficient Learning — the BBC’s Bayesian quiz engine
In this article, I’m going to give an overview of Bayesian statistics and talk about how we utilise user data to personalise and improve BBC Bitesize’s Efficient Learning GCSE quiz.
Example
Let’s start with an example for context.
Suppose you flip a coin 3 times and get heads each time. Is the coin biased?
For most people the answer will be no, but why?
When determining the answer to this question people use two pieces of information:
- the outcomes of the 3 coin flips
- their presumed knowledge about coins being fair
A normal (legal tender) coin is unbiased and has equal chance of producing heads or tails, that’s why we use it to make decisions. It’s also pretty unusual to get a non-normal coin (The Royal Mint estimates that just over 1 in 40 coins is counterfeit). So when making the above decision you are weighing up how likely you are to get the observed 3 heads from a normal coin versus how likely it is that you have a coin that biases towards heads.
