Answer to Question #341925 in Statistics and Probability for Mario

Question #341925

A GROUP OF STUDENT GOT THE FOLLOWING SCORES IN A TEST 6, 9, 12, 15, 18, AND 21. CONSIDER SAMPLE SIZE 3 THAT CAN BE DRAWN FROM THIS POPULATION.

1
Expert's answer
2022-05-18T06:50:05-0400

We have population values 6,9,12,15,18,21, population size N=6 and sample size n=3.

Mean of population "(\\mu)" = "\\dfrac{6+9+12+15+18+21}{6}=13.5"

Variance of population 


"\\sigma^2=\\dfrac{\\Sigma(x_i-\\bar{x})^2}{n}=\\dfrac{1}{6}(56.25+20.25+2.25"


"+2.25+20.25+56.25)=26.25"

"\\sigma=\\sqrt{\\sigma^2}=\\sqrt{26.25}\\approx5.1235"

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=^{6}C_3=20."

"\\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 & 6,9,18 & 11 \\\\\n \\hdashline\n 4 & 6,9,21 & 12 \\\\\n \\hdashline\n 5 & 6,12,15 & 11 \\\\\n \\hdashline\n 6 & 6,12,18 & 12 \\\\\n \\hdashline\n 7 & 6,12, 21 & 13 \\\\\n \\hdashline\n 8 & 6,15,18 & 13 \\\\\n \\hdashline\n 9 & 6,15,21 & 14 \\\\\n \\hdashline\n 10 & 6, 18,21 & 15 \\\\\n \\hdashline\n 11 & 9,12,15 & 12 \\\\\n \\hdashline\n 12 & 9, 12,18 & 13 \\\\\n \\hdashline\n 13 & 9, 12, 21 & 14 \\\\\n \\hdashline\n 14 & 9,15,18 & 14 \\\\\n \\hdashline\n 15 & 9,15,21 & 15 \\\\\n \\hdashline\n 16 & 9, 18,21 & 16 \\\\\n \\hdashline\n 17 & 12, 15,18 & 15 \\\\\n \\hdashline\n 18 & 12, 15,21 & 16 \\\\\n \\hdashline\n 19 & 12, 18,21 & 17 \\\\\n \\hdashline\n 20 & 15, 18,21 & 18 \\\\\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\/20 & 9\/20 & 81\/20 \\\\\n \\hdashline\n 10 & 1\/20 & 10\/20 & 100\/20 \\\\\n \\hdashline\n 11 & 2\/20 & 22\/20 & 242\/20 \\\\\n \\hdashline\n 12 & 3\/20 & 36\/20 & 432\/20 \\\\\n \\hdashline\n 13 & 3\/20 & 39\/20 & 507\/20 \\\\\n \\hdashline\n 14 & 3\/20 & 42\/20 & 588\/20 \\\\\n \\hdashline\n 15 & 3\/20 & 45\/20 & 675\/20 \\\\\n \\hdashline\n 16 & 2\/20 & 32\/20 & 512\/20 \\\\\n \\hdashline\n 17 & 1\/20 & 17\/20 & 289\/20 \\\\\n \\hdashline\n 18 & 1\/20 & 18\/20 & 324\/20 \\\\\n \\hdashline\n\\end{array}"



Mean of sampling distribution 

"\\mu_{\\bar{X}}=E(\\bar{X})=\\sum\\bar{X}_if(\\bar{X}_i)=\\dfrac{270}{20}=13.5=\\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{3750}{20}-(13.5)^2=5.25= \\dfrac{\\sigma^2}{n}(\\dfrac{N-n}{N-1})"

"\\sigma_{\\bar{X}}=\\sqrt{5.25}\\approx2.2913"


Need a fast expert's response?

Submit order

and get a quick answer at the best price

for any assignment or question with DETAILED EXPLANATIONS!

Comments

No comments. Be the first!

Leave a comment

LATEST TUTORIALS
New on Blog
APPROVED BY CLIENTS