Bayes Theorem Review

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In the previos node, you figured out Bayes Theorem and used it to calculate the probability of your coin being weighted knowing that it landed on heads. You did this by looking at the fraction of heads probabilities which came from weighted coins. We will now look at this formula more closely.

(Hover over the parts of Bayes Theorem for more info.)

P(W|H) =

P(H) = P(H|W)*P(W) + P(H|¬W)*P(¬W)

In our example, 10% of coins were weighted and had an 80% chance of landing on heads. They make up 15% of the total prior head probabilites, P(H). See chart:

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