Question #347501

Consider a population consisting of 1 2 3 4 and 5 suppose samples of size 2 are drawn from this population. Describes the sampling distribution of the sample mean INSTRUCTION 1.Determaine the number of possible samples of size n=2 2.List all possible sample and their corresponding means 3.Construct the sampling distribution of the sample means 4.Compute the mean of the distribution of the sample means.

Expert's answer

1. We have population values 1,2,3,4,5, population size N=5 and sample size n=2.

Mean of population (μ)(\mu) = 1+2+3+4+55=3\dfrac{1+2+3+4+5}{5}=3

Variance of population 



σ2=Σ(xixˉ)2n=4+1+0+1+45=2\sigma^2=\dfrac{\Sigma(x_i-\bar{x})^2}{n}=\dfrac{4+1+0+1+4}{5}=2



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 NCn=5C2=10.^{N}C_n=^{5}C_2=10.

noSampleSamplemean (xˉ)11,23/221,34/231,45/241,56/252,35/262,46/272,57/283,47/293,58/2104,59/2\def\arraystretch{1.5} \begin{array}{c:c:c:c:c} no & Sample & Sample \\ & & mean\ (\bar{x}) \\ \hline 1 & 1,2 & 3/2 \\ \hdashline 2 & 1,3 & 4/2 \\ \hdashline 3 & 1,4 & 5/2 \\ \hdashline 4 & 1,5 & 6/2 \\ \hdashline 5 & 2,3 & 5/2 \\ \hdashline 6 & 2,4 & 6/2 \\ \hdashline 7 & 2,5 & 7/2 \\ \hdashline 8 & 3,4 & 7/2 \\ \hdashline 9 & 3,5 & 8/2 \\ \hdashline 10 & 4,5 & 9/2 \\ \hdashline \end{array}



3.


Xˉf(Xˉ)Xˉf(Xˉ)Xˉ2f(Xˉ)3/21/103/209/404/21/104/2016/405/22/1010/2050/406/22/1012/2072/407/22/1014/2098/408/21/108/2064/409/21/109/2081/40\def\arraystretch{1.5} \begin{array}{c:c:c:c:c} \bar{X} & f(\bar{X}) &\bar{X} f(\bar{X}) & \bar{X}^2f(\bar{X}) \\ \hline 3/2 & 1/10 & 3/20 & 9/40 \\ \hdashline 4/2 & 1/10 & 4/20 & 16/40 \\ \hdashline 5/2 & 2/10 & 10/20 & 50/40 \\ \hdashline 6/2 & 2/10 & 12/20 & 72/40 \\ \hdashline 7/2 & 2/10 & 14/20 & 98/40 \\ \hdashline 8/2 & 1/10 & 8/20 & 64/40 \\ \hdashline 9/2 & 1/10 & 9/20 & 81/40 \\ \hdashline \end{array}



4. Mean of sampling distribution 


μXˉ=E(Xˉ)=Xˉif(Xˉi)=6020=3=μ\mu_{\bar{X}}=E(\bar{X})=\sum\bar{X}_if(\bar{X}_i)=\dfrac{60}{20}=3=\mu



The variance of sampling distribution 


Var(Xˉ)=σXˉ2=Xˉi2f(Xˉi)[Xˉif(Xˉi)]2Var(\bar{X})=\sigma^2_{\bar{X}}=\sum\bar{X}_i^2f(\bar{X}_i)-\big[\sum\bar{X}_if(\bar{X}_i)\big]^2=39040(3)2=34=σ2n(NnN1)=\dfrac{390}{40}-(3)^2=\dfrac{3}{4}= \dfrac{\sigma^2}{n}(\dfrac{N-n}{N-1})

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