This Exam P sample reference tests Discrete Random Variables. One individual's accident count has mean 0.24, second moment 0.32, and variance 0.2624. Independence makes the group variance 144(0.2624)=37.7856, which rounds to choice C.
These notes identify the calculation error associated with each wrong letter when that error is reproducible.
AThis first finds the correct aggregate variance but then divides it by √144 = 12, giving 37.7856/12 = 3.1488. Variances of independent observations add; they do not receive a final standard-error division.
BThis is the expected total, 144 E[X] = 144(0.24) = 34.56, rather than its variance.
DThis uses the raw second moment alone: 144 E[X²] = 144(0.32) = 46.08. It omits the subtraction of (E[X])² for each policyholder.
EThis adds rather than subtracts the squared mean, yielding 144[0.32 + (0.24)²] = 54.3744. The variance identity is E[X²] − (E[X])².
Original practice · fully worked
Original variant: compound shipment credits
A depot receives a Poisson-distributed number N of shipment batches per hour with mean 20. Each batch independently earns a credit W of 0, 1, or 3 points with probabilities 0.50, 0.30, and 0.20, respectively. The batch credits are independent of N. Let S be the total credit earned in one hour. Calculate the variance of S.
A 16.2
B 18.0
C 25.8
D 42.0
E 67.8
Variant answer in brief
A compound Poisson total satisfies Var(S)=E[N]E[W²]. Since E[W²]=2.1, the variance is 20(2.1)=42, so choice D is correct.
Setup
Setup
Express the hourly credit as a random sum of independent batch credits.
S=i=1∑NWi,N∼Poisson(20)
Model
Model
Find both the mean and second raw moment of one credit, which separate the two sources of compound-sum variation.
E[W]=0(0.50)+1(0.30)+3(0.20)=0.90
E[W2]=0+1(0.30)+9(0.20)=2.10
Var(W)=2.10−(0.90)2=1.29
Compute
Compute
Apply total variance; for a Poisson count, its mean and variance are both 20.
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