Consider a population consisting of 2,6,8,0 and 1. Suppose samples of size 2 are drawn from this population. Find the Mean and Variance of the sampling distribution of sample means.
We have population values 0,1,2,6,8, population size N=5 and sample size n=2.
Mean of population "(\\mu)" = "\\dfrac{0+1+2+6+8}{5}=3.4"
Variance of population
The number of possible samples which can be drawn without replacement is "^{N}C_n=^{5}C_2=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 & 0,1 & 1\/2 \\\\\n \\hdashline\n 2 & 0,2 & 2\/2 \\\\\n \\hdashline\n 3 & 0,6 & 6\/2\\\\\n \\hdashline\n 4 & 0,8 & 8\/2 \\\\\n \\hdashline\n 5 & 1,2 & 3\/2 \\\\\n \\hdashline\n 6 & 1,6 & 7\/2 \\\\\n \\hdashline\n 7 & 1,8 & 9\/2 \\\\\n \\hdashline\n 8 & 2,6 & 8\/2 \\\\\n \\hdashline\n 9 & 2,8 & 10\/2 \\\\\n \\hdashline\n 10 & 6,8 & 14\/2 \\\\\n \\hdashline\n\\end{array}"Mean of sampling distribution
"\\mu_{\\bar{X}}=E(\\bar{X})=\\sum\\bar{X}_if(\\bar{X}_i)=\\dfrac{68}{20}=3.4=\\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{604}{40}-(3.4)^2=3.54= \\dfrac{\\sigma^2}{n}(\\dfrac{N-n}{N-1})""\\sigma_{\\bar{X}}=\\sqrt{3.54}\\approx1.881489"
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