This Exam P sample reference tests Normal Distribution. The first loss probability is Φ(-2) because its standard deviation is half the common mean. Scaling that probability by 0.9 and inverting the normal CDF gives a second z-magnitude of 2.0440, hence a standard-deviation ratio of 0.9785, choice C.
These notes identify the calculation error associated with each wrong letter when that error is reproducible.
AThe value 0.49 is approximately sigma_B/mu=1/2.044, not the requested ratio sigma_B/sigma_A. Since sigma_A=mu/2, that quantity must be doubled.
BThe value 0.90 simply copies the loss-probability multiplier. Normal tail probabilities do not scale linearly with standard deviations.
DThe value 1.11 results from setting the second z-score to 0.9(-2) and taking 2/1.8. The probability, not the z-score, is multiplied by 0.9.
EThe value 1.71 would imply a second loss z-magnitude near 1.17 and a loss probability near 0.12, far above the required 0.02048.
Original practice · fully worked
Original variant: calibrate a Gaussian gauge from a central tolerance
The measurement error of a thickness gauge is normally distributed with mean zero and an unknown standard deviation. Ninety percent of its errors lie between -4 and 4 micrometers. Calculate the probability that its error exceeds 6 micrometers.
A 0.0068
B 0.0136
C 0.0273
D 0.0500
E 0.9932
Variant answer in brief
Symmetry makes 4 micrometers the 95th percentile, so the standard deviation is 4/z_0.95. The 6-micrometer threshold has z-score 1.5z_0.95, and its upper tail is 0.00681, choice A.
Setup
Setup
Let E denote the centered Gaussian measurement error.
E∼N(0,σ2)
Pr(−4≤E≤4)=0.90
Model
Model
The omitted probability is split equally between the two tails, so the upper endpoint is the 95th percentile.
Pr(E≤4)=0.95
σ4=z0.95=1.6448536
Compute
Compute
Calibrate the scale, standardize 6, and evaluate the one-sided upper tail.
σ=1.64485364=2.4318273
Pr(E>6)=1−Φ(σ6)=1−Φ(2.4672804)=0.0068072
Answer
Answer
The probability of an error above 6 micrometers is approximately 0.0068.
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