This Exam P sample reference tests Poisson Distribution. The first Poisson mean is the square of its standard deviation, or 2.25. The ratio of zero-count probabilities gives the second mean as 2.25-ln(1.1), whose square root is 1.467886, so choice D is correct.
These notes identify the calculation error associated with each wrong letter when that error is reproducible.
AThis reduces the second Poisson mean far too much by treating the 1.1 probability multiplier as a direct linear change instead of taking its logarithm.
BThis similarly applies the zero-probability ratio to the standard deviation scale rather than to the exponential zero-count probability.
CThis subtracts ln(1.1) directly from the first standard deviation, giving 1.4047, instead of subtracting it from the Poisson mean.
EThis increases the standard deviation even though a larger zero-count probability requires a smaller Poisson mean.
Original practice · fully worked
Original variant: sampled fault reports
A server's number N of fault reports in one cycle is Poisson. The coefficient of variation of N is 0.40. Each report is independently selected for a detailed audit with probability 0.25; let M be the selected count. Calculate the standard deviation of M.
A 0.40
B 0.63
C 0.79
D 1.25
E 2.50
Variant answer in brief
For a Poisson count, CV=1/√(λ), so CV 0.40 gives λ=6.25. Independent thinning makes M Poisson with mean 0.25(6.25)=1.5625 and standard deviation 1.25, so choice D is correct.
Setup
Setup
Recover the original Poisson mean from its coefficient of variation.
CV(N)=λλ=λ1=0.40
λ=0.4021=6.25
Model
Model
Independent selection thins a Poisson count to another Poisson count.
M∼Poisson(0.25λ)
E[M]=Var(M)=1.5625
Compute
Compute
Take the square root of the thinned-count variance.
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