Answer:
Sensitivity = 66.7% (C)
specificity= 98.0% (E)
positive predictive value = 80.0% (F)
Negative predictive value = 96.0% (D)
accuracy of the test = 94.5% (A)
Step-by-step explanation:
Given the data in the question;
Disease Present Disease Absent Total
Test Positive 24 6 30
Test Negative 12 288 300
Total 36 294 330
so A = 24, B = 6, C = 12 and D = 288
sensitivity = [A/(A+C)]×100 = [24/(24+12)]×100 = [24/36]×100
Sensitivity = 66.7% (C)
specificity= [D/(D+B)]×100 = [288/(288+6)]×100 = [288/294]×100
specificity= 98.0% (E)
positive predictive value = [A/(A+B)]×100 = [24/(24+6)]×100
= [24/30]×100
positive predictive value = 80.0% (F)
Negative predictive value = [D/(D+C)]×100 = [288/(288+12)]×100
= [288/300]×100
Negative predictive value = 96.0% (D)
accuracy of the test = [A+D/(A+B+C+D)]×100 = [24+288/(24+6+12+288)]×100
= [312/330]×100
accuracy of the test = 94.5% (A)
Nothing 33.3% (B)
