This Exam P sample reference tests Poisson Distribution. This problem converts an at-least-one Poisson probability through its zero-count complement. Solving 1-exp(-lambda_2)=2[1-exp(-0.5)] gives lambda_2=1.54618, so choice D.
These notes identify the calculation error associated with each wrong letter when that error is reproducible.
ADoubling the first mean gives 1.00, but the resulting at-least-one probability ratio is only 1.6065 because 1-exp(-λ) is nonlinear.
BSubstitution of 1.19 gives an at-least-one probability ratio of 1.7683 rather than the required 2.
CSubstitution of 1.23 gives a probability ratio of 1.7986. It still under-solves the nonlinear complement equation.
EUsing 2.00 produces a ratio of 2.1975, overshooting the stated probability multiplier.
Original practice · fully worked
Original variant: scale a Poisson alert probability
Alerts arrive according to a homogeneous Poisson process. During an eight-hour shift, the probability of at least one alert is 0.75. Calculate the probability of at least one alert during a two-hour interval.
A 0.0625
B 0.1875
C 0.2500
D 0.2929
E 0.7071
Variant answer in brief
The eight-hour zero probability is 0.25. A two-hour interval is one quarter as long, so its zero probability is 0.25⁽¹⁄⁴⁾=1/√(2), leaving at-least-one probability 0.292893 and choice D.
Setup
Setup
Let r be the hourly Poisson rate and convert the eight-hour observation to a zero-count probability.
Pr(N8=0)=1−0.75=0.25
e−8r=0.25
Model
Model
Use exponential time scaling to obtain the zero probability over one quarter of the duration.
e−2r=(e−8r)1/4=0.251/4=21
Compute
Compute
Take the complement of the two-hour zero-count probability.
Pr(N2≥1)=1−21=0.2928932188
Answer
Answer
The two-hour at-least-one probability is approximately 0.2929.
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