Question #341211

A population consists of the five numbers 2,5,6, 8,and 11. Consider samples of size 2 that can be drawn from the population.




A. List the possible samples and the corresponding mean.

1
Expert's answer
2022-05-16T16:30:12-0400

We have population values 2,5,6,8,11, population size N=5 and sample size n=2.

Mean of population (μ)(\mu) = 2+5+6+8+115=6.4\dfrac{2+5+6+8+11}{5}=6.4

Variance of population 


σ2=Σ(xixˉ)2n=15(19.36+1.96+0.16\sigma^2=\dfrac{\Sigma(x_i-\bar{x})^2}{n}=\dfrac{1}{5}(19.36+1.96+0.16


+2.56+21.16)=9.04+2.56+21.16)=9.04

σ=σ2=9.043.00666\sigma=\sqrt{\sigma^2}=\sqrt{9.04}\approx3.00666

A. 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)12,57/222,68/232,810/242,1113/255,611/265,813/275,1116/286,814/296,1117/2108,1119/2\def\arraystretch{1.5} \begin{array}{c:c:c:c:c} no & Sample & Sample \\ & & mean\ (\bar{x}) \\ \hline 1 & 2,5 & 7/2 \\ \hdashline 2 & 2,6 & 8/2 \\ \hdashline 3 & 2,8 & 10/2 \\ \hdashline 4 & 2,11 & 13/2 \\ \hdashline 5 & 5,6 & 11/2 \\ \hdashline 6 & 5,8 & 13/2 \\ \hdashline 7 & 5,11 & 16/2 \\ \hdashline 8 & 6,8 & 14/2 \\ \hdashline 9 & 6,11 & 17/2 \\ \hdashline 10 & 8,11 & 19/2 \\ \hdashline \end{array}





Xˉf(Xˉ)Xˉf(Xˉ)Xˉ2f(Xˉ)7/21/107/2049/408/21/108/2064/4010/21/1010/20100/4011/21/1011/20121/4013/22/1026/20338/4014/21/1014/20196/4016/21/1016/20256/4017/21/1017/20289/4019/21/1019/20361/40\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 7/2 & 1/10 & 7/20 & 49/40 \\ \hdashline 8/2 & 1/10 & 8/20 & 64/40 \\ \hdashline 10/2 & 1/10 & 10/20 & 100/40 \\ \hdashline 11/2 & 1/10 & 11/20 & 121/40 \\ \hdashline 13/2 & 2/10 & 26/20 & 338/40 \\ \hdashline 14/2 & 1/10 & 14/20 & 196/40 \\ \hdashline 16/2 & 1/10 & 16/20 & 256/40 \\ \hdashline 17/2 & 1/10 & 17/20 & 289/40 \\ \hdashline 19/2 & 1/10 & 19/20 & 361/40 \\ \hdashline \end{array}



Mean of sampling distribution 

μXˉ=E(Xˉ)=Xˉif(Xˉi)=12820=6.4=μ\mu_{\bar{X}}=E(\bar{X})=\sum\bar{X}_if(\bar{X}_i)=\dfrac{128}{20}=6.4=\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=177440(6.4)2=3.39=σ2n(NnN1)=\dfrac{1774}{40}-(6.4)^2=3.39= \dfrac{\sigma^2}{n}(\dfrac{N-n}{N-1})

σXˉ=3.391.8412\sigma_{\bar{X}}=\sqrt{3.39}\approx1.8412


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