This Exam P sample reference tests Poisson Distribution. The two independent Poisson counts must fall at or below their respective coverage limits. Their cumulative probabilities are 2.5e to the negative one and 1.3e to the negative 0.3, whose product is 0.885728; this is choice B.
These notes identify the calculation error associated with each wrong letter when that error is reproducible.
AThis multiplies the probabilities of landing exactly at both limits. Counts below either limit are also fully accommodated and must be included.
CThis is the complement of the probability that both limits are met, so it describes at least one count exceeding its allowance.
DThis multiplies the two exceedance probabilities and therefore requires both counts to be over their limits.
EThis is the complement of both counts exceeding their limits; it allows one count to exceed its limit and is therefore too broad.
Original practice · fully worked
Original variant: greenhouse service thresholds
During a greenhouse season, the number of pump resets is Poisson with mean 0.6, and the number of sensor recalibrations is Poisson with mean 1.4. The counts are independent. A basic service plan covers at most one reset and at most two recalibrations. Calculate the probability that every service event is covered.
A 0.020
B 0.080
C 0.268
D 0.732
E 0.980
Variant answer in brief
The two relevant Poisson cumulative probabilities are 1.6e to the negative 0.6 and 3.38e to the negative 1.4. Their independent product is 0.731893, which rounds to choice D.
Setup
Setup
Let R count pump resets and let C count sensor recalibrations during the season.
R∼Poisson(0.6),C∼Poisson(1.4)
{all events covered}={R≤1,C≤2}
Model
Model
Because the two counts are independent, multiply their within-threshold probabilities.
Pr(R≤1,C≤2)=Pr(R≤1)Pr(C≤2)
Compute
Compute
Evaluate each short Poisson sum and then multiply.
Pr(R≤1)=e−0.6(1+0.6)=1.6e−0.6
Pr(C≤2)=e−1.4(1+1.4+21.42)=3.38e−1.4
Pr(R≤1,C≤2)=5.408e−2=0.7318932117…
Answer
Answer
The service plan covers every event with probability about 0.732.
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