Compute probability an account is fake

Q: Compute probability an account is fake

This question evaluates understanding of conditional probability and Bayesian reasoning, specifically interpreting base rates alongside true positive and false positive rates to infer posterior probabilities for a flagged account.

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A platform uses an automated classifier to flag potentially fake accounts.

Assume:

Base rate: 2% of accounts are fake.
The classifier flags a fake account with probability 90% (true positive rate).
The classifier flags a real account with probability 5% (false positive rate).

If an account is flagged, what is the probability it is actually fake? Show your work and state any assumptions.

Compute probability an account is fake

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Compute probability an account is fake

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