We have population values "50,60,50,60,40," population size "N=5," and sample size "n=4." Thus, the number of possible samples which can be drawn without replacement is
"\\dbinom{5}{4}=5"
"mean=\\mu=\\dfrac{50+60+50+60+40}{5}=52""Variance=\\sigma^2""=\\dfrac{1}{5}((50-52)^2+(60-52)^2+(50-52)^2""+(60-52)^2+(40-52)^2)=56""\\def\\arraystretch{1.5}\n \\begin{array}{c:c:c}\n No & Sample & Mean \\\\ \\hline\n 1 & (50, 60, 50, 60) & 55 \\\\\n \\hdashline\n 2 & (50, 60, 50, 40) & 50 \\\\\n \\hdashline\n3 & (50, 60, 60, 40) & 52.5 \\\\\n \\hdashline\n4 & (50, 50, 60, 40) & 50 \\\\\n \\hdashline\n5 & (60, 50,60,40) & 52.5 \\\\\n \\hdashline\n\n\\end{array}"
The sampling distribution of the sample mean "\\bar{x}" and its mean and standard deviation are:
"\\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 50 & 2 & 2\/5 & 20 & 1000 \\\\\n \\hdashline\n 52.5 & 2 & 2\/5 & 21 & 1102.5 \\\\\n \\hdashline\n 55 & 1 & 1\/5 & 11 & 605 \\\\\n \\hdashline\n Total & 5 & 1 & 52 & 2707.5 \\\\\n \\hdashline\n\\end{array}""\\\\\\ \\\\\\text{Mean of the Sample Mean}=E(\\bar{X})=\\sum\\bar{x}f(\\bar{x})=52""\\text{Variance of Sample mean}=Var(\\bar{X})=\\sum\\bar{x}^2f(\\bar{x})-(\\sum\\bar{x}f(\\bar{x}))^2""=2707.5-52^2=3.5"
"\\text{Standard Deviation of the sample mean}SE=\\dfrac{s}{\\sqrt{n}}=\\dfrac{{3.5}}{\\sqrt{4}}=1.75"
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