Consider a population consisting of 1 2 3 4 and 5, suppose sample size of 2 are drawn from the population what is the mean, variance and standard deviation of the sampling distribution?
We have population values 1,2,3,4,5, population size N=5 and sample size n=2.
Mean of population "(\\mu)" = "\\dfrac{1+2+3+4+5}{5}=3"
Variance of populationÂ
"=2"
"\\sigma=\\sqrt{\\sigma^2}=\\sqrt{2}\\approx1.4142"
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 & 1,2 & 3\/2 \\\\\n \\hdashline\n 2 & 1,3 & 4\/2 \\\\\n \\hdashline\n 3 & 1,4 & 5\/2\\\\\n \\hdashline\n 4 & 1,5 & 6\/2 \\\\\n \\hdashline\n 5 & 2,3 & 5\/2 \\\\\n \\hdashline\n 6 & 2,4 & 6\/2 \\\\\n \\hdashline\n 7 & 2,5 & 7\/2 \\\\\n \\hdashline\n 8 & 3,4 & 7\/2 \\\\\n \\hdashline\n 9 & 3,5 & 8\/2 \\\\\n \\hdashline\n 10 & 4,5 & 9\/2 \\\\\n \\hdashline \n\\end{array}"Mean of sampling distributionÂ
"\\mu_{\\bar{X}}=E(\\bar{X})=\\sum\\bar{X}_if(\\bar{X}_i)=3=\\mu"The variance of sampling distributionÂ
"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{39}{4}-(3)^2=\\dfrac{3}{4}= \\dfrac{\\sigma^2}{n}(\\dfrac{N-n}{N-1})""\\sigma_{\\bar{X}}=\\sqrt{\\dfrac{3}{4}}=\\dfrac{\\sqrt{3}}{2}\\approx0.8660""\\mu_{\\bar{X}}=E(\\bar{X})=3=\\mu"
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