We have population values "1,3,5,7" population size "N=4" and sample size "n=2."
Thus, the number of possible samples which can be drawn without replacement is "\\dbinom{4}{2}=6."
"\\def\\arraystretch{1.5}\n \\begin{array}{c:c}\n Sample\\ values & Sample\\ mean(\\bar{X}) \\\\ \\hline\n 1,3 & 2\\\\\n \\hdashline\n 1,5 & 3\\\\\n \\hdashline\n 1,7 & 4\\\\\n \\hdashline\n 3,5 & 4\\\\\n \\hdashline\n 3.7 & 5\\\\\n \\hdashline\n 5,7 & 6\\\\\n \\hdashline\n\n\\end{array}"
The sampling distribution of the sample mean "\\bar{X}" is
"\\def\\arraystretch{1.5}\n \\begin{array}{c:c:c:c:c:c:c}\n & \\bar{X} & f & f(\\bar{X}) & Xf(\\bar{X})& X^2f(\\bar{X}) \\\\ \\hline\n & 2 & 1 & 1\/6 & 2\/6 & 4\/6\\\\\n \\hdashline\n & 3 & 1 & 1\/6 & 3\/6 & 9\/6 \\\\\n \\hdashline\n & 4 & 2 & 2\/6 & 8\/6 & 32\/6\\\\\n \\hdashline\n & 5 & 1 & 1\/6 & 5\/6 & 25\/6 \\\\\n \\hdashline\n & 6 & 1 & 1\/16 & 6\/6 & 36\/6 \\\\\n \\hdashline\n Sum= & & 6 & 1 & 4 & 53\/3\\\\\n \\hdashline\n\\end{array}"
"\\mu=\\dfrac{1+3+5+7}{4}=4"
"\\sigma^2=\\dfrac{1}{4}((1-4)^2+(3-4)^2+(5-4)^2+(7-4)^2)"
"=5"
Check
The mean of the sample means is
"\\mu_{\\bar{X}}=E(\\bar{X})=4=\\mu"
"Var(\\bar{X})=\\sigma^2_{\\bar{X}}=E(\\bar{X}^2)-(E(\\bar{X}))^2"
"=\\dfrac{53}{3}-(4)^2=\\dfrac{5}{3}"The standard deviation of the sample means is
"\\sigma_{\\bar{X}}=\\sqrt{\\sigma^2_{\\bar{X}}}=\\sqrt{5\/3}"
"\\dfrac{\\sigma^2}{n}\\cdot\\dfrac{N-n}{N-1}=\\dfrac{5}{3}\\cdot \\dfrac{4-2}{4-1}=\\sigma^2_{\\bar{X}}"
"\\mu_{\\bar{X}}=\\mu"
"\\sigma_{\\bar{X}}=\\dfrac{\\sigma}{\\sqrt{n}}\\sqrt{\\dfrac{N-n}{N-1}}"
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