This Exam P sample reference tests Mixture Distributions. The within-policy matching probabilities are 0.30 for type A and 0.25 for type B, giving an overall matching probability of 0.285. A Binomial(4,0.285) count equals one with probability 0.41670, choice D.
These notes identify the calculation error associated with each wrong letter when that error is reproducible.
AThe value 0.104 is approximately 0.285(0.715)³, the probability for one specified policy to match while the other three do not. It omits the four choices of the matching policy.
BThe value 0.250 is the matching probability for a type-B policy only. It does not average over policy types or consider four selections.
CThe value 0.285 is the matching probability for one randomly selected policy. It is the binomial trial probability, not the exactly-one count probability.
EThe value 0.739 is 1-(0.715)⁴, the probability that at least one of the four policies has matching counts. It also includes two, three, and four matches.
Original practice · fully worked
Original variant: infer a latent mode from matching codes
A device uses calibration mode A with probability 0.70 and mode B otherwise. Conditional on mode A, two independent output codes each take values 1, 2, and 3 with respective probabilities 60%, 25%, and 15%. Under mode B, each code is uniform on those three values. Given a matching pair of output codes, determine the chance that the device used mode A.
A 0.3333
B 0.4115
C 0.4450
D 0.7000
E 0.7570
Variant answer in brief
The matching probabilities are 0.445 in mode A and 1/3 in mode B. Bayes' rule gives 0.70(0.445)/[0.70(0.445)+0.30(1/3)]=0.7570, choice E.
Setup
Setup
Compute the collision probability under each calibration mode.
Pr(M∣A)=0.602+0.252+0.152=0.445
Pr(M∣B)=3(31)2=31
Model
Model
Combine the two modes to obtain the marginal matching probability.
Pr(M)=0.70(0.445)+0.30(31)=0.4115
Compute
Compute
Apply Bayes' rule to the observed match.
Pr(A∣M)=0.41150.70(0.445)
Pr(A∣M)=0.41150.3115=0.7569866
Answer
Answer
Given matching codes, mode A has posterior probability about 0.7570.
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