Answer to Question #345328 in Statistics and Probability for Hale

Question #345328

our hypothetical population contains the scores 5, 7, 9, and 11. determine the mean and variance of the sampling distribution of the sample mean., given that samples contain two scores drawn from the population with replacement.

1
Expert's answer
2022-05-27T14:42:37-0400

We have population values 5,7,9,11, population size N=4 and sample size n=2.

Mean of population "(\\mu)" = "\\dfrac{5+7+9+11}{4}=8"

Variance of population 


"\\sigma^2=\\dfrac{\\Sigma(x_i-\\bar{x})^2}{n}=\\dfrac{9+1+1+9}{4}=5"



Select a random sample of size 2 with replacement. We have a sample distribution of sample mean.

The number of possible samples which can be drawn with replacement is "N^n=4^2=16."

"\\def\\arraystretch{1.5}\n \\begin{array}{c:c:c:c:c}\n no & Sample & Sample \\\\\n& & mean\\ (\\bar{x})\n\\\\ \\hline\n 1 & 5,5 & 5 \\\\\n \\hdashline\n 2 & 5,7 & 6 \\\\\n \\hdashline\n 3 & 5,9 & 7 \\\\\n \\hdashline\n 4 & 5,11 & 8 \\\\\n \\hdashline\n 5 & 7,5 & 6 \\\\\n \\hdashline\n 6 & 7,7 & 7 \\\\\n \\hdashline\n 7 & 7,9 & 8 \\\\\n \\hdashline\n 8 & 7,11 & 9 \\\\\n \\hdashline\n 9 & 9,5 & 7 \\\\\n \\hdashline\n 10 & 9,7 & 8 \\\\\n \\hdashline\n 11 & 9,9 & 9 \\\\\n \\hdashline\n 12 & 9,11 & 10 \\\\\n \\hdashline\n 13 & 11,5 & 8 \\\\\n \\hdashline\n 14 & 11,7 & 9 \\\\\n \\hdashline\n 15 & 11,9 & 10 \\\\\n \\hdashline\n 16 & 11,11 & 11 \\\\\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 5 & 1\/16 & 5\/16 & 25\/16 \\\\\n \\hdashline\n 6 & 2\/16 & 12\/16 & 72\/16 \\\\\n \\hdashline\n 7 & 3\/16 & 21\/16 & 147\/16 \\\\\n \\hdashline\n 8 & 4\/16 & 32\/16 & 256\/16 \\\\\n \\hdashline\n 9 & 3\/16 & 27\/16 & 243\/16 \\\\\n \\hdashline\n 10 & 2\/16 & 20\/16 & 200\/16 \\\\\n \\hdashline\n 11 & 1\/16 & 11\/16 & 121\/16 \\\\\n \\hdashline\n\\end{array}"



Mean of sampling distribution 



"\\mu_{\\bar{X}}=E(\\bar{X})=\\sum\\bar{X}_if(\\bar{X}_i)=\\dfrac{128}{16}=8=\\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{1064}{16}-(8)^2=2.5= \\dfrac{\\sigma^2}{n}"

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