This Exam P sample reference tests Continuous Random Variables. The density has separate linear branches on the negative and positive parts of its support. Integrating those branches gives E[X]=28/15 and E[X²]=34/5, hence Var(X)=746/225=3.3156 and choice C is correct.
These notes identify the calculation error associated with each wrong letter when that error is reproducible.
AThe value 0.25 is a small-variance decoy that can look plausible after underweighting the distribution's tails; no standard single algebraic error was identified that reproduces it exactly.
BUsing the correct mean but assigning the negative-side second-moment contribution the wrong sign gives 6-(28/15)²=2.5156.
DMis-evaluating the negative-side first-moment contribution as -0.5 rather than -4/15 gives 6.8-(49/30)²=4.1322.
EThis is E[X²]-E[X]=34/5-28/15=4.9333, which subtracts the mean rather than its square.
Original practice · fully worked
Original variant: sensor-error survival model
A nonnegative sensor-error magnitude W has survival function P(W>w)=(1-w/6)² for 0≤w≤6, with survival probability zero above 6. Calculate the standard deviation of W.
A 1.000
B 1.414
C 2.000
D 2.449
E 6.000
Variant answer in brief
Tail integrals give E[W]=2 and E[W²]=6. Thus Var(W)=6-4=2 and SD(W)=√(2)=1.414, so choice B is correct.
Setup
Setup
Use the nonnegative-variable tail identities for the first two moments.
E[W]=∫0∞Pr(W>w)dw
E[W2]=2∫0∞wPr(W>w)dw
Model
Model
The survival function vanishes above 6, so both integrations stop at that endpoint.
E[W]=∫06(1−6w)2dw
E[W2]=2∫06w(1−6w)2dw
Compute
Compute
Evaluate the tail integrals, form the variance, and take its positive square root.
E[W]=2,E[W2]=6
Var(W)=6−22=2
SD(W)=2=1.41421356…
Answer
Answer
The sensor-error standard deviation is approximately 1.414.
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