My way of remembering formulas for specificity and sensitivity is that sPecificity has false Positive in it and seNsitivity has false Negative. Then the other variable is the opposite.
So the formula for sPecificity = true negative / (false Positive + true negative)
In this case, the true negative (tested negative and are actually normal) = 113
False positive (tested positive but are actually normal) = 1
submitted by โcassdawg(1780)
My way of remembering formulas for specificity and sensitivity is that sPecificity has false Positive in it and seNsitivity has false Negative. Then the other variable is the opposite.
So the formula for sPecificity = true negative / (false Positive + true negative)
Specificity = (113) / (113+1) = 113/114 = 0.99123 = 99.123%
NOTE: Negative and positive predictive value have the name of the variables used in them!
FA2020 p257