Answer to Question #344717 in Statistics and Probability for Deth

Question #344717

This item is 10 points. A population consists of the five measurements 1, 5, 3, 8, and 10 . Suppose samples of size 2 are drawn from this population. 

Compute and find the following:

1) Find the variance of the population.

2) Find the variance of the sampling distribution. 

1
Expert's answer
2022-05-25T17:22:43-0400

1) We have population values 1,3,5,8,10, population size N=5 and sample size n=2.

Mean of population "(\\mu)" = "\\dfrac{1+3+5+8+10}{5}=5.4"

Variance of population 


"\\sigma^2=\\dfrac{\\Sigma(x_i-\\bar{x})^2}{n}=\\dfrac{1}{5}(19.36+5.76""+0.16+6.76+21.16)=10.64"



2) Select a random sample of size 2 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_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 & 1,3 & 4\/2 \\\\\n \\hdashline\n 2 & 1,5 & 6\/2 \\\\\n \\hdashline\n 3 & 1,8 & 9\/2 \\\\\n \\hdashline\n 4 & 1,10 & 11\/2 \\\\\n \\hdashline\n 5 & 3,5 & 8\/2 \\\\\n \\hdashline\n 6 & 3,8 & 11\/2 \\\\\n \\hdashline\n 7 & 3,10 & 13\/2 \\\\\n \\hdashline\n 8 & 5,8 & 13\/2 \\\\\n \\hdashline\n 9 & 5,10 & 15\/2 \\\\\n \\hdashline\n 10 & 8,10 & 18\/2 \\\\\n \\hdashline\n\\end{array}"




"\\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 4\/2 & 1\/10 & 4\/20 & 16\/40 \\\\\n \\hdashline\n 6\/2 & 1\/10 & 6\/20 & 36\/40 \\\\\n \\hdashline\n 8\/2 & 1\/10 & 8\/20 & 64\/40 \\\\\n \\hdashline\n 9\/2 & 1\/10 & 9\/20 & 81\/40 \\\\\n \\hdashline\n 11\/2 & 2\/10 & 22\/20 & 242\/40 \\\\\n \\hdashline\n 13\/2 & 2\/10 & 26\/20 & 338\/40 \\\\\n \\hdashline\n 15\/2 & 1\/10 & 15\/20 & 225\/40 \\\\\n \\hdashline\n 18\/2 & 1\/10 & 18\/20 & 324\/40 \\\\\n \\hdashline\n\n\\end{array}"



Mean of sampling distribution 


"\\mu_{\\bar{X}}=E(\\bar{X})=\\sum\\bar{X}_if(\\bar{X}_i)=\\dfrac{108}{20}=5.4=\\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{1316}{40}-(5.4)^2=3.99= \\dfrac{\\sigma^2}{n}(\\dfrac{N-n}{N-1})"

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