This Exam P sample reference tests Sums of Independent Random Variables. Let l be the low-variability count. Independence makes total variance 0.5²l+5.5²(76-l), and setting this equal to 43² gives l=15. Therefore choice B is correct.
These notes identify the calculation error associated with each wrong letter when that error is reproducible.
AAdding individual standard deviations linearly gives one member in the high-variability class; this choice both uses that invalid rule and reports the wrong class.
CThis assumes an equal 38-38 split without using the supplied total standard deviation.
DThis is the correctly implied high-variability count 76-15=61, but the requested count is for the other class.
EThis comes from the invalid linear equation 0.5l+5.5(76-l)=43, which gives l=75 instead of adding variances.
Original practice · fully worked
Original variant: infer sensor noise
A monitoring array contains 12 independent low-noise channels and 8 independent high-noise channels. Each low-noise reading has standard deviation 2, while each high-noise reading has the same unknown standard deviation s. The standard deviation of the sum of all 20 readings is 10. Calculate s.
A 2.000
B 2.550
C 3.082
D 6.500
E 10.000
Variant answer in brief
Independent variances add, so 10²=12(2²)+8s². This gives s²=6.5 and s=√(6.5)=2.5495, making choice B correct.
Setup
Setup
Translate each standard deviation into a variance contribution.
Var(Li)=22=4,Var(Hi)=s2
Model
Model
Independence makes the variance of the full sum equal the sum of all channel variances.
102=12(4)+8s2
Compute
Compute
Remove the low-noise contribution, divide by eight, and take the positive square root.
8s2=100−48=52
s2=6.5
s=6.5=2.549509757
Answer
Answer
The high-noise channel standard deviation rounds to 2.550.
The 3108-page Probability Proof Manual reorganizes 718 verified Exam P solutions by syllabus skill and adds formula proofs, error patterns, and original worked practice.