We have population values "3,5,8,9," population size "N=4"
"\\mu=\\dfrac{3+5+8+9}{4}=6.25""\\sigma^2=\\dfrac{1}{4}((3-6.25)^2+(5-6.25)^2+(8-6.25)^2"
"+(9-6.25)^2)=5.6875"
We have population values "3,5,8,19," population size "N=4" and sample size "n=3." Thus, the number of possible samples which can be drawn without replacement is
"\\dbinom{N}{n}=\\dbinom{4}{3}=4""\\def\\arraystretch{1.5}\n \\begin{array}{c:c:c}\n Sample & Sample & Sample \\ mean \\\\\n No. & values & (\\bar{X}) \\\\ \\hline\n 1 & 3,5,8 & 16\/3 \\\\\n \\hdashline\n 2 & 3,5,9 & 17\/3 \\\\\n \\hdashline\n 3 & 3,8,9 & 20\/3 \\\\\n \\hdashline\n 4 & 5,8,9 & 22\/3 \\\\\n \\hline\n\\end{array}"The sampling distribution of the sample means.
"\\def\\arraystretch{1.5}\n \\begin{array}{c:c:c:c:c:c}\n& \\bar{X} & f & f(\\bar{X}) & \\bar{X}f(\\bar{X})& \\bar{X}^2f(\\bar{X}) \\\\ \\hline\n & 16\/3 & 1 & 1\/4 & 6.25 & 256\/36 \\\\\n \\hdashline\n & 17\/3 & 1& 1\/4 & 17\/12 & 289\/36 \\\\\n \\hdashline\n & 20\/3 & 1 & 1\/4 & 20\/12 & 400\/36 \\\\\n \\hdashline\n & 22\/3 & 1& 1\/4 & 22\/12 & 484\/36 \\\\\n \\hdashline\n Total & & 4 & 1 & 6.25 & 1429\/36 \\\\ \\hline\n\\end{array}"
The mean of the sampling distribution of the sample means is equal to the the mean of the population.
"E(\\bar{X})=\\mu_{\\bar{X}}=6.25=\\mu"
"Var(\\bar{X})=\\sum(\\bar{X}-\\mu)^2"
"=\\sum\\bar{X}^2f(\\bar{X})-(\\sum\\bar{X}f(\\bar{X}))^2"
"=\\dfrac{1429}{36}-(6.25)^2=\\dfrac{91}{144}"
Verification:
"Var(\\bar{X})=\\dfrac{\\sigma^2}{n}(\\dfrac{N-n}{N-1})=\\dfrac{5.6875}{3}(\\dfrac{4-3}{4-1})"
"=\\dfrac{91}{144}, True"
"\\sum(\\bar{X}-\\mu)^2=\\dfrac{91}{144}"
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