This Exam P sample reference tests Sums of Independent Random Variables. Independence lets the second component inherit mean 0.8 and variance 1.35 from the stated totals. Its coefficient of variation is √(1.35)/0.8 = 1.45237, so the answer is E.
How to solve this Sums of Independent Random Variables question
Setup
Setup
Recover the mean of the unobserved component by subtracting component means.
E[Z]=E[X]−E[Y]=2.00−1.20=0.80
Model
Model
For independent components, the variance of their sum is the sum of their variances.
Var(Z)=Var(X)−Var(Y)
Var(Z)=2.25−0.90=1.35
Compute
Compute
Divide the component standard deviation by its mean.
CV(Z)=0.801.35=1.452368754…
Answer
Answer
The coefficient of variation rounds to 1.45.
1.45(E)
Test the method on unseen problems
Probability Multivariate & Risk Models Practice Workbook
30 original multivariate random variables problems with complete solutions and wrong-choice analysis. Written for Exam P, not copied from the SOA set. One-time $19 PDF.
These notes identify the calculation error associated with each wrong letter when that error is reproducible.
AThis results from mixing the first component's mean with the second component's variance rather than using a consistent standard-deviation-to-mean ratio.
BThis uses an incorrect variance subtraction or divides by a total-scale quantity instead of the mean of the requested component.
CThis is the standard deviation √(1.35) by itself, before division by the component mean.
DThis is the variance 1.35, not the coefficient of variation.
Original practice · fully worked
Original variant: weighted fabrication cost
A fabrication shop models two independent random resource loads, X and Y. Their means are 3 and 5 units, and their standard deviations are 1 and 2 units, respectively. A batch cost index is defined by C=2X+Y. Calculate the coefficient of variation of C.
A 0.223
B 0.257
C 0.354
D 0.364
E 0.727
Answer and calculation
The weighted cost has mean 2(3)+5=11. Independence gives variance 2 squared times 1 squared plus 2 squared, or 8. Therefore its coefficient of variation is √(8)/11=0.2571297, so choice B is correct.
Setup
Setup
Apply linearity of expectation to the weighted cost index.
E[C]=2E[X]+E[Y]=2(3)+5=11
Model
Model
Independence removes the covariance term, while the coefficient on X is squared in the variance.
Var(C)=22Var(X)+Var(Y)
Var(C)=4(12)+22=8
Compute
Compute
Divide the standard deviation of the cost index by its mean.
CV(C)=E[C]Var(C)
CV(C)=118=0.2571297386…
Answer
Answer
The cost-index coefficient of variation rounds to 0.257.