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Applying Bayess rule, we have odds(smoker | cancer) = odds(smoker) * p(cancer | smoker) / p(cancer | non-smoker) Rearranging terms, we can solve for the risk ratio: p(cancer | smoker) / p(cancer | non-smoker) = odds(smoker | cancer) / odds(smoker) = 16 Thats the answer I had in mind, but let me address an objection raised by one poll respondent, who chose Other because, You cant draw casual inferences from observational data without certain assumptions which Im unwilling to make. Thats true

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The tax is sold as a mechanism for raising government revenue and improving health outcomes by discouraging consumption of cigarettes

The AAD recommend the following medical options for reducing scars: steroid injections, which may ease pain and reduce the size of keloid and other scars laser treatments, which can reduce redness, pain, and hardness of keloid and other scars