This Exam P sample reference tests Uniform Distribution. A uniform percentile lies the stated fraction of the interval width above the lower endpoint. At probability 0.80 this is a+0.8(b-a)=0.2a+0.8b, which is choice B.
These notes identify the calculation error associated with each wrong letter when that error is reproducible.
AThe expression a+0.8b adds 80% of the upper endpoint instead of 80% of the interval width b-a, so it double-counts part of the lower-endpoint shift.
CThe expression 0.8a+0.2b is a+0.2(b-a), the 20th percentile; it reverses the endpoint weights.
DThe expression 0.8(b-a) measures the correct distance from the lower endpoint but omits the required starting value a.
EThe expression 0.8(a+b) scales the sum of the endpoints. It fails the translation check because shifting both endpoints by c would shift it by 1.6c rather than c.
Original practice · fully worked
Original variant: calibrating an unknown uniform range
A machine's calibration score is uniformly distributed on an unknown interval. Its 25th percentile is 18 and its 75th percentile is 34. Calculate the probability that a calibration score exceeds 30.
A 0.125
B 0.250
C 0.375
D 0.625
E 0.750
Variant answer in brief
The 16-point interquartile gap is half the full uniform width, so the support is [10,42]. The tail above 30 has length 12 out of 32, giving 0.375 and choice C.
Setup
Setup
For a uniform distribution, a percentile difference equals the same fraction of the full support width.
q0.75−q0.25=0.50(U−L)
Model
Model
Recover the width and then the two endpoints from either stated percentile.
34−18=0.50(U−L)⇒U−L=32
18=L+0.25(32)⇒L=10,U=42
Compute
Compute
Uniform probability is proportional to interval length.
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