Final answer:
The probability of being diabetic, receiving a negative result, and being mistakenly classified as non-diabetic is 12%. Conversely, the chance of a non-diabetic person being misclassified as diabetic is 15%, which are calculated based on the complement of NPV and specificity, respectively.
Step-by-step explanation:
The question is related to the probability and statistics involved in a medical testing scenario, specifically concerning diabetes diagnosis using specificity and negative predictive value (NPV). Specificity refers to the probability that a test correctly identifies non-diabetic individuals as such, while NPV represents the probability that someone who receives a negative test result actually does not have diabetes.
1. The probability of a person being diabetic, receiving a negative test result, and being classified as non-diabetic involves the false negative rate, which is the complement of NPV. Thus, the probability can be calculated as 1 - NPV, giving us 1 - 0.88 = 0.12 or 12%.
2. To find the probability of being non-diabetic and classified as diabetic, we must look at the false positive rate, which is the complement of specificity. Calculating this gives us 1 - Specificity, so 1 - 0.85 = 0.15 or 15%.
It is important to note that these probabilities provide insights into the performance of the diagnostic test and are critical for understanding the implications of test results within a clinical setting.