Birth weighs at a local hospital have a normal distribution with a mean of 110 ounces & a standard deviation of 15 ounces.
a. What’s the proportion of infants with births weighs above 125 ounces?
b. What’s the proportion of infants with birth weights between 125 ounces & 140 ounces?
a. What’s the proportion of infants with births weighs above 125 ounces?
b. What’s the proportion of infants with birth weights between 125 ounces & 140 ounces?
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Let X be birth weights at a local hospital.
X ∼ n(110; 15)
a)
P(X ≥ 125) = P((X - 110)/15 ≥ (125 - 110)/15) = P(Z ≥ 1) = 0.1587
b)
P(125 ≤ X ≤ 140) = P((125 - 110)/15 ≤ (X - 110)/15 ≤ (140 - 110)/15) = P(1 ≤ Z ≤ 2) =
P(Z ≤ 2) - P(Z ≤ 1) = 0.9772 - 0.8413 = 0.1359
X ∼ n(110; 15)
a)
P(X ≥ 125) = P((X - 110)/15 ≥ (125 - 110)/15) = P(Z ≥ 1) = 0.1587
b)
P(125 ≤ X ≤ 140) = P((125 - 110)/15 ≤ (X - 110)/15 ≤ (140 - 110)/15) = P(1 ≤ Z ≤ 2) =
P(Z ≤ 2) - P(Z ≤ 1) = 0.9772 - 0.8413 = 0.1359
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use your graphing calculator.
for a do: 1- normalcdf (.0000001,125,110,15)
for b do: normalcdf (.000001,140,110,15) - normalcdf (.0000001,125,110,15)
The .000001 doesn't have to be exact. just an extremely miniscule number.
for a do: 1- normalcdf (.0000001,125,110,15)
for b do: normalcdf (.000001,140,110,15) - normalcdf (.0000001,125,110,15)
The .000001 doesn't have to be exact. just an extremely miniscule number.