Mean
"\\mu=\\dfrac{2+6+8+0+1}{5}=3.4"Variance
"\\sigma^2=\\dfrac{1}{5}\\big((2-3.4)^2+(6-2.4)^2+(8-3.4)^2""(0-3.4)^2+(1-3.4)^2\\big)=9.44"
Standard deviation
"\\sigma=\\sqrt{\\sigma^2}=\\sqrt{9.44}\\approx3.0725"
We have population values "2,6,8,0,1" population size "N=5" and sample size "n=4." Thus, the number of possible samples which can be drawn without replacement is
"\\dbinom{N}{n}=\\dbinom{5}{4}=5""\\def\\arraystretch{1.5}\n \\begin{array}{c:c:c}\n Sample & Sample & Sample \\ mean \\\\\n No. & values & (\\bar{X}) \\\\ \\hline\n 1 & 2,6, 8, 0 & 4 \\\\\n \\hdashline\n 2 & 2,6,8,1 & 4.25 \\\\\n \\hdashline\n 3 & 2,6,0,1 & 2.25 \\\\\n \\hdashline\n 4 & 2,8,0,1 & 2.75 \\\\\n \\hdashline\n 5 & 6,8,0,1 & 3.75 \\\\\n \\hline\n\\end{array}"
"\\def\\arraystretch{1.5}\n \\begin{array}{c:c:c:c:c}\n \\bar{X} & f & f(\\bar{X}) & \\bar{X}f(\\bar{X})& \\bar{X}^2f(\\bar{X}) \\\\ \\hline\n 9\/4 & 1& 1\/5 & 9\/20 & 81\/80 \\\\\n \\hdashline\n 11\/4 & 1 & 1\/5 & 11\/20 & 121\/80 \\\\\n \\hdashline\n 15\/4 & 1 & 1\/5 & 15\/20 & 225\/80 \\\\\n \\hdashline\n 4 & 1 & 1\/5 & 16\/20 & 256\/80 \\\\\n \\hdashline\n 17\/4 & 1& 1\/5 & 17\/20 & 289\/80 \\\\\n \\hdashline\n Total & 5 & 1 & 68\/20 & 972\/80 \\\\ \\hline\n\\end{array}"
"E(\\bar{X})=\\sum\\bar{X}f(\\bar{X})=\\dfrac{68}{20}=3.4"The mean of the sampling distribution of the sample means is equal to the
the mean of the population.
"E(\\bar{X})=3.4=\\mu"
"Var(\\bar{X})=\\sum\\bar{X}^2f(\\bar{X})-(\\sum\\bar{X}f(\\bar{X}))^2"
"=\\dfrac{972}{80}-(\\dfrac{68}{20})^2=\\dfrac{472}{800}=\\dfrac{59}{100}=0.59"
"\\sqrt{Var(\\bar{X})}=\\sqrt{\\dfrac{59}{100}}\\approx0.7681"Verification:
"Var(\\bar{X})=\\dfrac{\\sigma^2}{n}(\\dfrac{N-n}{N-1})=\\dfrac{9.44}{4}(\\dfrac{5-4}{5-1})""=0.59, True"
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