Classical probability goes from causes to effects: knowing the coin is fair, what is the chance of heads? Often the problem is the reverse. We see the effects and want to know about the cause: after seeing certain results, what can we say about the coin? The first to treat this probability of causes mathematically was the English clergyman Thomas Bayes, in a paper published after his death, in 1763. Laplace arrived at the same ideas independently in 1774, without knowing of Bayes, and it was he who developed and applied them.