A new medical screening test is used to detect a rare, non-life-threatening condition. If a person has this condition, the test always detects it. Approximately 0.2% of the population has the condition. Over many trials, the test returns a positive result 6% of the time. Julio takes the test and gets a positive result. To the nearest tenth of a percent, what is the probability that Julio actually has the condition?

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A new medical screening test is used to detect a rare, non-life-threatening condition. If a person has this condition, the test always detects it. Approximately 0.2% of the population has the condition. Over many trials, the test returns a positive result 6% of the time. Julio takes the test and gets a positive result. To the nearest tenth of a percent, what is the probability that Julio actually has the condition?

Mathematics
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@triciaal Earlier when I was working on those percent problems, were you there and trying them also? I think I have an idea, but I will need you to check it.

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|dw:1437440977572:dw|
That is not what I got. That isn't even how I interpreted the question.
sorry don't care for stats
@Nnesha help?
@marihelenh percent ok probability part of stats need to be verified
D = person has disease T = test returns positive `If a person has this condition, the test always detects it` means P(T|D) = 1 `Approximately 0.2% of the population has the condition` ---> P(D) = 0.002 `Over many trials, the test returns a positive result 6% of the time` ---> P(T) = 0.06 Use Bayes Theorem to get \[\Large P(D|T) = \frac{P(T|D)*P(D)}{P(T)}\] \[\Large P(D|T) = \frac{1*0.002}{0.06}\] \[\Large P(D|T) \approx 0.0333\] So if the test returns positive, then there is a 3.33% chance (roughly) that he has the condition.
Thank you all!
Aahhh, I would have had it right golly gee! That was what I got but in a much simpler way.

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