Let "\\overline{x}" be the sample mean and "\\mu" be the population mean. We have "\\sigma=2.7" (standard deviation of the population), "n=66" (size of the sample). We should find "P(|\\overline{x}-\\mu|\\geq 0.75)" and "P(\\overline{x}-\\mu \\geq 0.75)".
Let "X_1,\\ldots,X_{66}" is our sample (each "X_i" is a random variable). Consider "\\overline{x}=\\frac{1}{66}(X_1+\\ldots+X_{66})" (the sample mean "\\overline{x}" is a random variable).
Random variable "\\overline{x}" is normally distributed with mean "\\mu" and standard deviation "\\frac{\\sigma}{\\sqrt{n}}=\\frac{2.7}{\\sqrt{66}}".
Then random variable "\\overline{x}-\\mu" is normally distributed with mean 0 and standard deviation "\\frac{2.7}{\\sqrt{66}}."
ii) "P(\\overline{x}-\\mu\\geq 0.75)=P(Z\\geq\\frac{0.75}{\\frac{2.7}{\\sqrt{66}}})=1-P(Z\\leq 2.25)=1-0.4877=0.5123."
i)
i"P(|\\overline{x}-\\mu|\\geq 0.75)=P(|Z|\\geq\\frac{0.75}{\\frac{2.7}{\\sqrt{66}}})=1-P(|Z|\\leq\\frac{0.75}{\\frac{2.7}{\\sqrt{66}}})=\\\\\n=1-P(-\\frac{0.75}{\\frac{2.7}{\\sqrt{66}}}\\leq Z\\leq\\frac{0.75}{\\frac{2.7}{\\sqrt{66}}})=1-(0.4877+0.4877)=0.0246."
Random variable Z has a standard distribution.
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