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Suppose that 1% of all people have a particular disease. A test for the disease is 99% accurate. This means that a person who tests positive for the disease has a 99% chance of actually having the disease, while a person who tests negative for the disease has a 99% chance of not having the disease. If a person tests positive for the disease, what is the chance (rounded to the nearest hundredth) that he or she actually has the disease?
Please read through the case scenario shown below to gain an understanding of the background information and the research study
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