This Exam P sample reference tests Normal Distribution. This problem recovers μ/σ from one normal positive-tail probability and then forms an independent two-variable sum. Its standardized mean is 4Φ⁻¹(0.67)/√(10), giving probability 0.7110 and choice A.
These notes identify the calculation error associated with each wrong letter when that error is reproducible.
BA probability of 0.73 corresponds to z=0.6128 and an implied total standard deviation 2.871sigma rather than √(10)sigma=3.162sigma.
CTreating the second standard-deviation multiplier 3 as a variance multiplier gives total variance 4sigma² and Phi[2(mu/sigma)]=0.8105, near 0.81.
DA probability of 0.92 corresponds to z=1.4051 and an implied total standard deviation only 1.252sigma, far below the correct √(10)sigma.
EIgnoring the second variance entirely gives Phi[4(mu/sigma)]=0.9607, near 0.96.
Original practice · fully worked
Original variant: conditional paired sensor reading
Sensor readings X and Y are jointly normal with means 10 and 20, standard deviations 2 and 3, and correlation 0.5. Given that X=12, calculate the conditional probability that Y exceeds 22.
A 0.2525
B 0.4237
C 0.5000
D 0.5763
E 0.7475
Variant answer in brief
Given X=12, the conditional normal mean of Y is 21.5 and its standard deviation is 3sqrt(0.75)=2.5981. The upper tail above 22 is 0.4237, so choice B.
Setup
Setup
Use the conditional-mean formula for a bivariate normal pair.
E[Y∣X=12]=20+0.523(12−10)=21.5
Model
Model
Conditioning reduces the variance by the squared correlation.
Var(Y∣X=12)=32(1−0.52)=6.75
SD(Y∣X=12)=2.598076211…
Compute
Compute
Standardize the threshold under the conditional normal distribution.
z=6.7522−21.5=0.192450090…
Pr(Y>22∣X=12)=1−Φ(z)=0.423694830…
Answer
Answer
The requested conditional upper-tail probability is about 0.4237.
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