a. If "n>30," the Central Limit Theorem can be used.
Let "X_1,X_2,...,X_n" be a random sample from a distribution with mean "\\mu" and variance "\\sigma^2." Then if "n" is sufficiently large, "\\bar{X}" has approximately a normal distribution with "\\mu_{\\bar{X}}=\\mu" and "\\sigma_{\\bar{X}}=\\sigma\/\\sqrt{n}."
b.
"Var(\\bar{X})=\\sigma^2\/n=3^2\/100=0.09\\ (ounces^2)"
"\\sigma_{\\bar{X}}=\\sigma\/\\sqrt{n}=3\/\\sqrt{100}=0.3 \\ ounces"
c.
"=1-0.5=0.5"
d.
e.
"=P\\big(Z<{9-8\\over 0.3}\\big)-P\\big(Z<{7-8\\over 0.3}\\big)\\approx"
"\\approx P(Z<3.3333)- P(Z<-3.3333)\\approx"
"\\approx0.999571-0.000429\\approx0.999142"
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