This Exam P sample reference tests Normal Distribution. A variance of 4 gives standard deviation 2. The 12th-percentile standard-normal score is about -1.175, so transforming back gives 7.650, choice B.
These notes identify the calculation error associated with each wrong letter when that error is reproducible.
AThe value 5.30 uses 4 as the standard deviation: 10+4(-1.175)=5.30. The given 4 is a variance, so the standard deviation is 2.
CThe value 8.41 corresponds to a standardized score near -0.795, not the 12th-percentile score -1.175.
DThe value 12.35 uses the correct magnitude but the wrong sign, placing a lower-tail percentile above the mean.
EThe value 14.70 combines both errors: it treats the variance as a standard deviation and reverses the lower-tail sign.
Original practice · fully worked
Original variant: recover a normal scale from symmetric percentiles
A calibrated sensor reading is normally distributed. Its 20th percentile is 25.792 and its 80th percentile is 34.208. Using these values, calculate the probability that a reading exceeds 38.
A 0.0228
B 0.0548
C 0.1000
D 0.9452
E 0.9772
Variant answer in brief
Symmetry gives mean 30, while the 80th-percentile offset identifies a standard deviation essentially equal to 5. The threshold 38 has z-score 1.6, whose upper tail is 0.0548, choice B.
Setup
Setup
Use symmetry of the two supplied percentiles to identify the mean.
μ=225.792+34.208=30
Model
Model
The 80th-percentile standard-normal score calibrates the scale.
z0.80=0.8416212
σ=0.841621234.208−30=4.9998739
Compute
Compute
Standardize 38 and evaluate the corresponding upper tail.
z=4.999873938−30=1.6000404
Pr(X>38)=1−Φ(1.6000404)=0.0547948
Answer
Answer
The exceedance probability is approximately 0.0548.
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