This Exam P sample reference tests Poisson Distribution. Writing the two Poisson cumulative probabilities cancels their common exponential factor. The stated ratio produces a quadratic equation with positive root 4. Because a Poisson mean equals its parameter, the answer is 4.0, choice B.
These notes identify the calculation error associated with each wrong letter when that error is reproducible.
AThe value 3.2 comes from replacing one plus the mean by the mean when rearranging the ratio. The omitted constant materially changes the quadratic.
CA mean of 4.2 makes the cumulative-probability ratio about 2.696, not 2.6.
DA mean of 5.0 makes the ratio about 3.083, well above the supplied value.
EA mean of 5.2 makes the ratio about 3.181 and likewise fails the calibration equation.
Original practice · fully worked
Original variant: calibrate a flaw count from expected pairs
The number N of flaws found on a panel has a Poisson distribution. The expected number of unordered pairs that can be formed from the flaws on one panel is 6. Calculate the probability that a panel has no flaws.
A 0.0025
B 0.0313
C 0.0863
D 0.1769
E 0.9687
Variant answer in brief
For a Poisson count, the expected number of unordered pairs is one-half the squared mean. Setting this equal to 6 gives mean square root of 12, so the zero-flaw probability is approximately 0.0313 and choice B.
Setup
Setup
Write the pair count as a falling-factorial function of N.
(2N)=2N(N−1)
Model
Model
Use the second factorial moment of a Poisson variable.
E[N(N−1)]=λ2
6=2λ2,λ=12
Compute
Compute
Evaluate the zero-count mass at the recovered mean.
Pr(N=0)=e−12=0.0313011132…
Answer
Answer
The zero-flaw probability is approximately 0.0313.
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