This Exam P sample reference tests Bayes' Theorem. A positive result has probability 0.90 for the target group and 0.20 for its complement. Weighting by the 0.30 prevalence gives a target-group contribution of 0.27 out of 0.41 total positives, so the posterior is 0.658537 and choice C.
These notes identify the calculation error associated with each wrong letter when that error is reproducible.
AThis multiplies the sensitivity and false-positive rate, 0.90(0.20)=0.18. Those likelihoods belong to mutually exclusive underlying states and should not be multiplied.
BThis repeats the 0.30 prevalence before observing the test result. A positive result changes the probability because the two positive likelihoods differ.
DThis is 1-0.90(0.20)=0.82, the complement of an irrelevant product of the two state-specific likelihoods.
EThis reports the sensitivity P(positive given the target state)=0.90. The requested conditioning direction is reversed.
Original practice · fully worked
Original variant: passenger-selected shuttle type
In a large fleet, 55% of the vehicles are minibuses with 18 seats and 45% are coaches with 42 seats. Every vehicle is carrying a full load. One passenger is selected uniformly from all passengers in the fleet. Calculate the probability that the selected passenger is riding in a coach.
A 0.344
B 0.450
C 0.550
D 0.656
E 0.700
Variant answer in brief
Passenger selection weights each vehicle type by its seat count. The coach contribution is 0.45(42)=18.9 seats per fleet vehicle out of 28.8 total, giving 21/32=0.65625 and choice D.
Setup
Setup
A passenger is more likely to come from a vehicle type that contributes more occupied seats. Form the occupied-seat weights.
wM=0.55(18)=9.9
wC=0.45(42)=18.9
Model
Model
Conditioning on a uniformly selected passenger normalizes the vehicle-type weights by total occupied seats.
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