This Exam P sample reference tests Binomial Distribution. The number of accident-producing errors is binomial with four trials and probability 0.30. An accident is unreimbursed only when that count exceeds two, so the required tail is 0.0837 and choice B is correct.
These notes identify the calculation error associated with each wrong letter when that error is reproducible.
AThe value 0.03 comes from (0.30)³=0.027, which fixes three particular errors as accidents and omits both their possible locations and the four-accident case.
CThe value 0.24 is (0.70)⁴=0.2401, the probability that none of the four errors produces an accident, not an upper-tail probability.
DThe value 0.32 is close to P(N=0)+P(N=3)=0.2401+0.0756=0.3157; the no-accident case cannot create an unreimbursed accident.
EThe value 0.41 is P(N=1)=4(0.30)(0.70)³=0.4116, which describes exactly one accident and remains entirely within the reimbursement limit.
Original practice · fully worked
Original variant: conditional batch acceptance
Eight independent sensors are tested, and each sensor passes with probability 0.75. A shipment is released only when at least six sensors pass. Given that the shipment is released, calculate the probability that exactly seven sensors passed.
A 0.2670
B 0.3934
C 0.6785
D 0.7273
E 0.7500
Variant answer in brief
Condition the seven-pass mass on the release event. Dividing P(X=7) by P(X at least 6) gives 24/61=0.3934, so choice B is correct.
Setup
Setup
Let X be the number of sensors that pass the independent tests.
X∼Binomial(8,0.75)
Model
Model
Exactly seven passes is contained in the release event, so the conditional probability is a ratio of one mass to an upper tail.
Pr(X=7∣X≥6)=Pr(X=6)+Pr(X=7)+Pr(X=8)Pr(X=7)
Compute
Compute
Evaluate the three binomial masses and form the ratio.
The 3108-page Probability Proof Manual reorganizes 718 verified Exam P solutions by syllabus skill and adds formula proofs, error patterns, and original worked practice.