Let ܺ denote the number of scores on a test. If ܺ is normally
distributed with mean 100 and variance 225, find the probability
that ܺ does not exceed 130.
"\\sigma" = "\\sqrt{\\sigma^2}" = "\\sqrt{225}" =15
The probability that X < 30 is equal to the blue area under the curve.
Since "\\mu=100" and "\\sigma=15" we have:
P(X<130) = P(X-"\\mu" < 130-100) = P"(\\frac{X-\\mu}{\\sigma}<\\frac{130-100}{15})"
Since "\\frac{X-\\mu}{\\sigma} = Z" and "\\frac{130-100}{15} = 2" we have:
P(X<130) = P(Z<2)
Use the standard normal table
to conclude that:
P(Z<2) = 0.9772
Answer: P = 0.9772.
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