We have population values 2,4,5,9,20, population size N=5 and sample size n=3.
Mean of population "(\\mu)" = "\\dfrac{2+4+5+9+20}{5}=8"
Variance of population
"\\sigma^2=\\dfrac{\\Sigma(x_i-\\bar{x})^2}{N}=\\dfrac{36+16+9+1+144}{5}=41.2""\\sigma=\\sqrt{\\sigma^2}=\\sqrt{41.2}\\approx6.4187"
The number of possible samples which can be drawn without replacement is "^{N}C_n=^{5}C_3=10."
"\\def\\arraystretch{1.5}\n \\begin{array}{c:c:c:c:c}\n no & Sample & Sample \\\\\n& & mean\\ (\\bar{x})\n\\\\ \\hline\n 1 & 2,4,5 & 11\/3 \\\\\n \\hdashline\n 2 & 2,4,9 & 15\/3 \\\\\n \\hdashline\n 3 & 2,4,20 & 26\/3\\\\\n \\hdashline\n 4 & 2,5,9 & 16\/3 \\\\\n \\hdashline\n 5 & 2,5,20 & 27\/3 \\\\\n \\hdashline\n 6 & 2,9,20 & 31\/3 \\\\\n \\hdashline\n 7 & 4,5,9 & 18\/3 \\\\\n \\hdashline\n 8 & 4,5,20 & 29\/3 \\\\\n \\hdashline\n 9 & 4,9,20 & 33\/3 \\\\\n \\hdashline\n 10 & 5,9,20 & 34\/3 \\\\\n \\hdashline\n\\end{array}"
"\\def\\arraystretch{1.5}\n \\begin{array}{c:c:c:c:c}\n \\bar{X} & f(\\bar{X}) &\\bar{X} f(\\bar{X})& \\bar{X}^2f(\\bar{X}) \n\\\\ \\hline\n11\/3 & 1\/10 & 11\/30 & 121\/90 \\\\\n \\hdashline\n 15\/3 & 1\/10 & 15\/30 & 225\/90 \\\\\n \\hdashline\n 16\/3 & 1\/10 & 16\/30 & 256\/90 \\\\\n \\hdashline\n 18\/3 & 1\/10 & 18\/30 & 324\/90 \\\\\n \\hdashline\n 26\/3 & 1\/10 & 26\/30 & 676\/90 \\\\\n \\hdashline\n 27\/3 & 1\/10 & 27\/30 & 729\/90 \\\\\n \\hdashline\n 29\/3 & 1\/10 & 29\/30 & 841\/90 \\\\\n \\hdashline\n 31\/3 & 1\/10 & 31\/30 & 961\/90 \\\\\n \\hdashline\n 33\/3 & 1\/10 & 33\/30 & 1089\/90 \\\\\n \\hdashline\n34\/3 & 1\/10 & 34\/30 & 1156\/90 \\\\\n \\hdashline\n\\end{array}"
Mean of sampling distribution
"\\mu_{\\bar{X}}=E(\\bar{X})=\\sum\\bar{X}_if(\\bar{X}_i)=8=\\mu"
The variance of sampling distribution
"Var(\\bar{X})=\\sigma^2_{\\bar{X}}=\\sum\\bar{X}_i^2f(\\bar{X}_i)-\\big[\\sum\\bar{X}_if(\\bar{X}_i)\\big]^2""=\\dfrac{6378}{90}-(8)^2=\\dfrac{103}{15}= \\dfrac{\\sigma^2}{n}(\\dfrac{N-n}{N-1})""\\sigma_{\\bar{X}}=\\sqrt{\\dfrac{103}{15}}\\approx2.6204"
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