This Exam P sample reference tests Continuous Distributions. Normalizing the power density gives a CDF proportional to x raised to a+1. The supplied CDF value calibrates that exponent near 2.5, and the upper tail beyond 4 is 0.4276, choice B.
These notes identify the calculation error associated with each wrong letter when that error is reproducible.
AThe value 0.404 corresponds to using an exponent near 2.31 rather than the exponent fixed by the supplied CDF point. The log calibration gives 2.5003.
CThe value 0.500 treats 4 as a median without deriving that claim from the density. The calibrated CDF at 4 is about 0.5724.
DThe value 0.572 is F(4), the probability below 4. The question requires its complement.
EThe value 0.596 is the complement of distractor A and inherits the same miscalibrated power before also selecting the wrong side of the cutoff.
Original practice · fully worked
Original variant: infer a bounded power law from a conditional fraction
A quality score X lies between 0 and 12 and has cumulative distribution F(x)=(x/12)ᵏ on that interval, where k is positive. Among scores no greater than 9, the fraction no greater than 6 is 4/9. Determine the median score.
A 6.000
B 8.000
C 8.485
D 9.000
E 10.392
Variant answer in brief
The conditional fraction gives (2/3)ᵏ=4/9, so k=2. Solving F(m)=1/2 then gives m=12/√(2)=8.485, choice C.
Setup
Setup
Express the supplied conditional fraction as a ratio of CDF values.
Pr(X≤6∣X≤9)=F(9)F(6)=94
Model
Model
Substitute the power-form CDF; the common endpoint cancels.
(9/12)k(6/12)k=(32)k=94
Compute
Compute
The calibration gives k=2, after which the median equation is immediate.
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