This Exam P sample reference tests Poisson Distribution. This asks for the most probable count of a Poisson variable with mean 2.5. Adjacent probability ratios show that the mass increases through count 2 and decreases at count 3, so the unique mode is 2 and choice C.
These notes identify the calculation error associated with each wrong letter when that error is reproducible.
AThe value 1 can result from subtracting one standard deviation from the mean and rounding, but that quantity does not locate a Poisson mode.
BThe value 1.5 subtracts one from the mean. The Poisson mode for a noninteger mean is its integer floor, not the mean minus one.
DThe value 2.5 is the mean of the distribution. A count must be an integer, and the mean need not be the mode.
EThe value 3 rounds or takes the ceiling of the mean. The adjacent-mass ratio is already below one at count three.
Original practice · fully worked
Original variant: modal median of three calibration readings
Three independent calibration panels each display an integer selected uniformly from 1 through 5. The controller records M, the median of the three displayed values. Calculate the mode of M.
A 1 display unit
B 2 display units
C 3 display units
D 4 display units
E 5 display units
Variant answer in brief
The median CDF at m is the probability that at least two of three panels are at most m. Differencing it gives masses 13, 31, 37, 31, and 13 out of 125, so the unique mode is 3 and choice C.
Setup
Setup
Let q=m/5 be the probability that one panel displays at most m.
q=Pr(Xi≤m)=5m
Model
Model
The median is at most m exactly when at least two of the three panels are at most m.
Pr(M≤m)=3q2(1−q)+q3=3q2−2q3
Compute
Compute
Difference consecutive CDF values and compare the five masses.
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