When scientists measure, they use the metric system.
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The great/best answer is d. By definition the proportion of false-positive results among those who test positive is 1 minus the positive predictive value. If this number is lower in population A, then population A has a higher positive predictive value. As the disease prevalence increases, the positive predictive value increases. Population A has a higher positive predictive value; therefore, the disease must be more prevalent in population A.
<span>Answer a is not correct since adequate information is provided to infer the explanation for the finding. Answers b and e are incorrect since specificity is a characteristic of a test and does not change when the test is applied to different populations with varying disease prevalence. Answer c is incorrect since the prevalence of disease must be higher in population A as the positive predictive value is higher in population A</span>
Answer:
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Explanation:
<span>Lymphomas? Perhaps? I hope that helps
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