This Exam P sample reference tests Continuous Distributions. Intersecting the two interval events leaves 2<Y<3. Integrating the density gives probability 13/54 for that intersection and 13/27 for the conditioning interval 2<Y<4. Their ratio is 1/2, so choice D is correct.
These notes identify the calculation error associated with each wrong letter when that error is reproducible.
AThis does not result from consistently intersecting the target interval with the condition and dividing by the full conditioning probability.
BThis is the unnormalized numerator probability P(2<Y<3)=13/54, so it omits division by P(2<Y<4).
CThis is the conditioning probability P(2<Y<4)=13/27 rather than the requested conditional ratio.
EThis uses P(1<Y<3) as the numerator without intersecting it with 2<Y<4; dividing that larger probability by the conditioning probability gives about 0.885.
Original practice · fully worked
Original variant: conditional load median
A normalized equipment-load index X has density f(x)=x/18 for 0<x<6 and zero otherwise. Given that the load index exceeds 2, determine the median of the resulting conditional distribution.
A 3.000
B 4.000
C 4.243
D 4.472
E 4.690
Variant answer in brief
The CDF is x squared divided by 36. A conditional median m balances the probability mass on (2,m) and (m,6), giving m squared minus 4 equal to 36 minus m squared. Thus m=√(20)=4.472, choice D.
Setup
Setup
Integrate the density to obtain the distribution function on its support.
F(x)=∫0x18tdt=36x2,0<x<6
Model
Model
Let m be the conditional median above 2. Half of the conditional mass must lie between 2 and m.
1−F(2)F(m)−F(2)=21
Compute
Compute
Substitute the quadratic CDF and solve for the support value greater than 2.
1−4/36m2/36−4/36=21
m2−4=16
m=20=4.472135955…
Answer
Answer
The median after conditioning above 2 is approximately 4.472.
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