Find the mean of the set 7 10 14 17 20 of data and construct a sampling distribution by selecting 3 samples at a time
We have population values 7, 10, 14, 17, 20, population size N=5 and sample size n=3.
Mean of population "(\\mu)" = "\\dfrac{7+10+14+17+20}{5}=13.6"
Variance of population
"\\sigma=\\sqrt{\\sigma^2}=\\sqrt{21.84}\\approx4.6733"
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 & 7,10,14 & 31\/3 \\\\\n \\hdashline\n 2 & 7, 10, 17 & 34\/3 \\\\\n \\hdashline\n 3 & 7,10,20 & 37\/3\\\\\n \\hdashline\n 4 & 7,14,17 & 38\/3 \\\\\n \\hdashline\n 5 & 7,14,20 & 41\/3 \\\\\n \\hdashline\n 6 & 7,17,20 & 44\/3 \\\\\n \\hdashline\n 7 & 10,14,17 & 41\/3 \\\\\n \\hdashline\n 8 & 10,14,20 & 44\/3 \\\\\n \\hdashline\n 9 & 10,17,20 & 47\/3 \\\\\n \\hdashline\n 10 & 14,17,20 & 51\/3 \\\\\n \\hdashline\n\\end{array}"Mean of sampling distribution
"\\mu_{\\bar{X}}=E(\\bar{X})=\\sum\\bar{X}_if(\\bar{X}_i)=13.6=\\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{16974}{90}-(13.6)^2=\\dfrac{327.6}{90}=3.64= \\dfrac{\\sigma^2}{n}(\\dfrac{N-n}{N-1})""\\sigma_{\\bar{X}}=\\sqrt{3.64}\\approx1.9079"
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