Condition: Antibodies 
Condition positive (CP)  Condition negative (CN)  

Test outcome positive (OP) 
Sensitivity
True positive

False positive

All OP

Test outcome negative (ON) 
False negative

Specificity
True negative

All ON

Base Rate

All CP

All CN

All Tested
100.00

P(HE) = =
= = = = ≃ %;
Suppose, you do a COVID19 blood test at home. Test kits are now available. Vendors guarantee around 99% specificity and 9799% sensitivity. What does this mean? A vast majority of subjects, including academics would answer: “if the test finds antibodies, I am 99% sure it's true” and accordingly “if I have no antibodies, in 97% of the cases the test will come out negative”.
But it is wrong! Imagine, you were falsely tested positive (meaning, you have antibodies and are  probably  safe) and you go to work and don't wear a mask! This means, the test would cause you to run a big risk.
Let's do the math: suppose, the overall probabilty, the base rate, of having antibodies is 0.003 (US: 1.68 MM infected out of 330 MM are 0.005, Germany: 0.18MM / 83MM = .002  data by end of May, 2020).
Suppose 10000 people are doing the test you have done. According to the base rate (.01), 100 of them will have antibodies. 99 of these get a positive test outcome (as the specificity is .99). The other 9900 should yield a negative test outcome. However, since the test specificity is not 100%, but only 98%, from these 9900 will 9000*0.02 (.02 = 1  .98) yield a falsely positive outcome.
The result will come as a suprise! You gonna rub your eyes in disbelief! This app will help you to understand, what's going on here  before you learn the math. Toggle terms and definitions
Today's example: antibody COVID19 tests. We are going to use three variables:
Then, we are dealing with two "binary" variables, meaning they can assume but two values: true or false.
Finally, the quantity we are interested in is called P(HE), meaning the probabilty of H given E (or, for H being true given that the there is evidence, namely a positve antibody test).
All this definitions and symbols may feel a little overwhelming. But the good new is: that's already it!