For a random variable,
X∼N(μ,σ2), z=X−μσ∼N(0,1)X \sim N(\mu,\sigma^2), \ z=\frac{X-\mu}{\sigma} \sim N(0,1) \newlineX∼N(μ,σ2), z=σX−μ∼N(0,1)
The given weight,
W∼N(60,92),Z=W−609∼N(0,1)P(Z>a)=0.69W \sim N(60,9^2), Z=\frac{W-60}{9} \sim N(0,1) \newline P(Z>a)=0.69W∼N(60,92),Z=9W−60∼N(0,1)P(Z>a)=0.69
From the normal distribution Z table,
a=−0.50,a=-0.50,a=−0.50,
P(Z>−0.5)=P(X−μσ>W−609)∵W=−0.5⋅9+60=55.5P(Z>-0.5)=P(\frac{X-\mu}{\sigma}>\frac{W-60}{9}) \newline \because W=-0.5 \cdot 9+60=55.5P(Z>−0.5)=P(σX−μ>9W−60)∵W=−0.5⋅9+60=55.5
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