a. Mean
"\\mu=\\dfrac{2+5+7+8}{4}=5.5"b. Variance
"\\sigma^2=\\dfrac{1}{4}\\big((2-5.5)^2+(5-5.5)^2+(7-5.5)^2"
"+(8-5.5)^2\\big)=\\dfrac{21}{4}=5.25"
c. Standard deviation
"\\sigma=\\sqrt{\\sigma^2}=\\sqrt{\\dfrac{21}{4}}=\\dfrac{\\sqrt{21}}{2}\\approx2.2913"
d. We have population values "2,5,7,8," population size "N=4" and sample size "n=2." Thus, the number of possible samples which can be drawn without replacement is
"\\dbinom{N}{n}=\\dbinom{4}{2}=6""\\def\\arraystretch{1.5}\n \\begin{array}{c:c:c}\n Sample & Sample & Sample \\ mean \\\\\n No. & values & (\\bar{X}) \\\\ \\hline\n 1 & 2,5 & 3.5 \\\\\n \\hdashline\n 2 & 2,7 & 4.5 \\\\\n \\hdashline\n 3 & 2,8 & 5 \\\\\n \\hdashline\n 4 & 5,7 & 6 \\\\\n \\hdashline\n 5 & 5,8 & 6.5 \\\\\n \\hdashline\n 6 & 7,8 & 7.5 \\\\\n \n \\hline\n\\end{array}"
The sampling distribution of the sample means.
"\\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 7\/2 & 1& 1\/6 & 7\/12 & 49\/24 \\\\\n \\hdashline\n 9\/2 & 1 & 1\/6 & 9\/12 & 81\/24 \\\\\n \\hdashline\n 5 & 1 & 1\/6 & 10\/12 & 100\/24 \\\\\n \\hdashline\n 6 & 1 & 1\/6 & 12\/12 & 144\/24 \\\\\n \\hdashline\n 13\/2 & 1& 1\/6 & 13\/12 & 169\/24 \\\\\n \\hdashline\n 15\/2 & 1 & 1\/6 & 15\/12 & 225\/24 \\\\\n \\hdashline\n Total & 6 & 1 & 66\/12 & 768\/24 \\\\ \\hline\n\\end{array}"
"E(\\bar{X})=\\sum\\bar{X}f(\\bar{X})=\\dfrac{66}{12}=5.5"The mean of the sampling distribution of the sample means is equal to the
the mean of the population.
"E(\\bar{X})=5.5=\\mu"
"Var(\\bar{X})=\\sum\\bar{X}^2f(\\bar{X})-(\\sum\\bar{X}f(\\bar{X}))^2"
"=\\dfrac{768}{24}-(\\dfrac{66}{12})^2=\\dfrac{42}{24}=\\dfrac{7}{4}=1.75"
"\\sqrt{Var(\\bar{X})}=\\sqrt{\\dfrac{7}{4}}=\\dfrac{\\sqrt{7}}{2}\\approx1.3229"
Verification:
"Var(\\bar{X})=\\dfrac{\\sigma^2}{n}(\\dfrac{N-n}{N-1})=\\dfrac{\\dfrac{21}{4}}{2}(\\dfrac{4-2}{4-1})"
"=\\dfrac{7}{4}=1.75, True"
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