What is the ratio of prior and posterior probabilities


It is said that Napoleon assessed probabilities at the battle of Waterloo in 1815. His hopes for victory depended on keeping the English and Prussian armies separated. Believing that they had not joined forces on the morning of the fateful battle, he indicated his belief that he had a 90% chance of defeating the English; P(Napoleon Wins=0.9) . When told later that the elements of the Prussian force had joined the English, Napoleon revised his opinion downward on the basis of this information, but his posterior probability was still 60%. P(Napoleon Wins|Prussian and English Join Forces)=0.6 .

Suppose Napoleon were using Bayes' theorem to revise his information. To do so, he would have had to make some judgments about P(Prussian and English Join Forces|Napoleon Wins) and P(Prussian and English Join Forces|Napoleon Loses). In particular, he would have had to judge the ratio of these two probabilities. Based on the prior and posterior probabilities given above, what is that ratio?

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Basic Statistics: What is the ratio of prior and posterior probabilities
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