Answer to Question #341338 in Statistics and Probability for Killua

Question #341338

A population consists of six values (6, 9, 12, 15, 18, and 21). (with illustration)

e. Determine the mean, variance and standard deviation of the sample mean.


1
Expert's answer
2022-05-16T16:35:30-0400

We have population values 6,9,12,15,21, population size N=5 and sample size n=3.

Mean of population "(\\mu)" = "\\dfrac{6+9+12+15+21}{5}=12.6"

Variance of population 


"\\sigma^2=\\dfrac{\\Sigma(x_i-\\bar{x})^2}{n}=\\dfrac{1}{5}(43.56+12.96+0.36"


"+5.76+70.56)=26.64"

"\\sigma=\\sqrt{\\sigma^2}=\\sqrt{26.64}\\approx5.1614"

A. Select a random sample of size 3 without replacement. We have a sample distribution of sample mean.

The number of possible samples which can be drawn without replacement is "^{N}C_n=^{5}C_3=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 & 6,9,12 & 9 \\\\\n \\hdashline\n 2 & 6,9,15 & 10 \\\\\n \\hdashline\n 3 & 6,9,21 & 12 \\\\\n \\hdashline\n 4 & 6,12,15 & 11 \\\\\n \\hdashline\n 5 & 6,12,21 & 13 \\\\\n \\hdashline\n 6 & 6,15,21 & 14 \\\\\n \\hdashline\n 7 & 9,12,15 & 12 \\\\\n \\hdashline\n 8 & 9,12,21 & 14 \\\\\n \\hdashline\n 9 & 9,15,21 & 15 \\\\\n \\hdashline\n 10 & 12,15,21 & 16 \\\\\n \\hdashline\n\\end{array}"



B.


"\\def\\arraystretch{1.5}\n \\begin{array}{c:c:c:c:c}\n \\bar{X} & f(\\bar{X}) &\\bar{X} f(\\bar{X}) & \\bar{X}^2f(\\bar{X})\n\\\\ \\hline\n 9 & 1\/10 & 9\/10 & 81\/10 \\\\\n \\hdashline\n 10 & 1\/10 & 10\/10 & 100\/10 \\\\\n \\hdashline\n 11 & 1\/10 & 11\/10 & 121\/10 \\\\\n \\hdashline\n 12 & 2\/10 & 24\/10 & 288\/10 \\\\\n \\hdashline\n 13 & 1\/10 & 13\/10 & 169\/10 \\\\\n \\hdashline\n 14 & 2\/10 & 28\/10 & 392\/10 \\\\\n \\hdashline\n 15 & 1\/10 & 15\/10 & 225\/10 \\\\\n \\hdashline\n 16 & 1\/10 & 16\/10 & 256\/10 \\\\\n \\hdashline\n\\end{array}"



Mean of sampling distribution 

"\\mu_{\\bar{X}}=E(\\bar{X})=\\sum\\bar{X}_if(\\bar{X}_i)=\\dfrac{126}{10}=12.6=\\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{1632}{10}-(12.6)^2=4.44= \\dfrac{\\sigma^2}{n}(\\dfrac{N-n}{N-1})"

"\\sigma_{\\bar{X}}=\\sqrt{4.44}\\approx2.1071"


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