Answer to Question #305337 in Statistics and Probability for Yyy

Question #305337

A population consistent of value 3,5,7 and 9





1)List all the possible of size n=3 when drawing with replacement and compute the mean of each sample





2) construct a sampling distribution of the mean





3) compute for the mean and variance of the of the sample means

1
Expert's answer
2022-03-03T17:58:36-0500

We have population values 3,5,7,93,5,7,9 population size N=4N=4 and sample size n=3.n=3.

Thus, the number of possible samples which can be drawn with replacement is 43=64.4^3=64.


Sample valuesSample mean(Xˉ)3,3,333,3,511/33,3,713/33,3,953,5,311/33,5,513/33,5,753,5,917/33,7,313/33,7,553,7,717/33,7,919/33,9,353,9,517/33,9,719/33,9,975,3,311/35,3,513/35,3,755,3,917/35,5,313/35,5,555,5,717/35,5,919/35,7,355,7,517/35,7,719/35,7,975,9,317/35,9,519/35,9,775,9,923/37,3,313/37,3,557,3,717/37,3,919/37,5,357,5,517/37,5,719/37,5,977,7,317/37,7,519/37,7,777,7,923/37,9,319/37,9,577,9,723/37,9,925/39,3,359,3,517/39,3,719/39,3,979,5,317/39,5,519/39,5,779,5,923/39,7,319/39,7,579,7,723/39,7,925/39,9,379,9,523/39,9,725/39,9,99\def\arraystretch{1.5} \begin{array}{c:c} Sample\ values & Sample\ mean(\bar{X}) \\ \hline 3,3,3 & 3\\ \hdashline 3,3,5 & 11/3\\ \hdashline 3,3,7 & 13/3\\ \hdashline 3,3,9 & 5\\ \hdashline 3,5,3 & 11/3\\ \hdashline 3,5,5 & 13/3\\ \hdashline 3,5,7 & 5\\ \hdashline 3,5,9 & 17/3\\ \hdashline 3,7,3 & 13/3\\ \hdashline 3,7,5 & 5\\ \hdashline 3,7,7 & 17/3\\ \hdashline 3,7,9 & 19/3\\ \hdashline 3,9,3 & 5\\ \hdashline 3,9,5 & 17/3\\ \hdashline 3,9,7 & 19/3\\ \hdashline 3,9,9 & 7\\ \hdashline 5,3,3 & 11/3\\ \hdashline 5,3,5 & 13/3\\ \hdashline 5,3,7 & 5\\ \hdashline 5,3,9 & 17/3\\ \hdashline 5,5,3 & 13/3\\ \hdashline 5,5,5 & 5\\ \hdashline 5,5,7 & 17/3\\ \hdashline 5,5,9 & 19/3\\ \hdashline 5,7,3 & 5\\ \hdashline 5,7,5 & 17/3\\ \hdashline 5,7,7 & 19/3\\ \hdashline 5,7,9 & 7\\ \hdashline 5,9,3 & 17/3\\ \hdashline 5,9,5 & 19/3\\ \hdashline 5,9,7 & 7\\ \hdashline 5,9,9 & 23/3\\ \hdashline 7,3,3 & 13/3\\ \hdashline 7,3,5 & 5\\ \hdashline 7,3,7 & 17/3\\ \hdashline 7,3,9 & 19/3\\ \hdashline 7,5,3 & 5\\ \hdashline 7,5,5 & 17/3\\ \hdashline 7,5,7 & 19/3\\ \hdashline 7,5,9 & 7\\ \hdashline 7,7,3 & 17/3\\ \hdashline 7,7,5 & 19/3\\ \hdashline 7,7,7 & 7\\ \hdashline 7,7,9 & 23/3\\ \hdashline 7,9,3 & 19/3\\ \hdashline 7,9,5 & 7\\ \hdashline 7,9,7 & 23/3\\ \hdashline 7,9,9 & 25/3\\ \hdashline 9,3,3 & 5\\ \hdashline 9,3,5 & 17/3\\ \hdashline 9,3,7 & 19/3\\ \hdashline 9,3,9 & 7\\ \hdashline 9,5,3 & 17/3\\ \hdashline 9,5,5 & 19/3\\ \hdashline 9,5,7 & 7\\ \hdashline 9,5,9 & 23/3\\ \hdashline 9,7,3 & 19/3\\ \hdashline 9,7,5 & 7\\ \hdashline 9,7,7 & 23/3\\ \hdashline 9,7,9 & 25/3\\ \hdashline 9,9,3 & 7\\ \hdashline 9,9,5 & 23/3\\ \hdashline 9,9,7 & 25/3\\ \hdashline 9,9,9 & 9\\ \hdashline \end{array}



2) The sampling distribution of the sample mean Xˉ\bar{X} is


Xˉff(Xˉ)Xf(Xˉ)X2f(Xˉ)311/643/6427/19211/333/6411/64121/19213/366/6426/64338/19251010/6450/64750/19217/31212/6468/641156/19219/31212/6476/641444/19271010/6470/641470/19223/366/6446/641058/19225/333/6425/64625/192911/169/64243/192Sum=6416113/3\def\arraystretch{1.5} \begin{array}{c:c:c:c:c:c:c} & \bar{X} & f & f(\bar{X}) & Xf(\bar{X})& X^2f(\bar{X}) \\ \hline & 3 & 1 & 1/64 & 3/64 & 27/192\\ \hdashline & 11/3 & 3 & 3/64 & 11/64 & 121/192 \\ \hdashline & 13/3 & 6 & 6/64 & 26/64 & 338/192\\ \hdashline & 5 & 10 & 10/64 & 50/64 & 750/192 \\ \hdashline & 17/3 & 12 & 12/64 & 68/64 & 1156/192 \\ \hdashline & 19/3 & 12 & 12/64 & 76/64 & 1444/192 \\ \hdashline & 7 & 10 & 10/64 & 70/64 & 1470/192 \\ \hdashline & 23/3 & 6 & 6/64 & 46/64 & 1058/192 \\ \hdashline & 25/3 & 3 & 3/64 & 25/64 & 625/192 \\ \hdashline & 9 & 1 & 1/16 & 9/64 & 243/192 \\ \hdashline Sum= & & 64 & 1 & 6 & 113/3\\ \hdashline \end{array}

μ=3+5+7+94=6\mu=\dfrac{3+5+7+9}{4}=6


σ2=14((36)2+(56)2+(76)2+(96)2)\sigma^2=\dfrac{1}{4}((3-6)^2+(5-6)^2+(7-6)^2+(9-6)^2)

=5=5


The mean of the sample means is


μXˉ=E(Xˉ)=6\mu_{\bar{X}}=E(\bar{X})=6




Var(Xˉ)=σXˉ2=E(Xˉ2)(E(Xˉ))2Var(\bar{X})=\sigma^2_{\bar{X}}=E(\bar{X}^2)-(E(\bar{X}))^2


=1133(6)2=53=\dfrac{113}{3}-(6)^2=\dfrac{5}{3}

μXˉ=μ\mu_{\bar{X}}=\mu

σXˉ2=σ2n\sigma_{\bar{X}}^2=\dfrac{\sigma^2}{n}


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