Question #347059

A group of 8 students in your class having the weight of 50, 52, 53, 54, 56, 57 58, and 60.


Expert's answer

We have population values 50, 52, 53, 54, 56, 57 58, 60, population size N=8 and sample size n=2.

Mean of population (μ)(\mu) = 

18(50+52+53+54+56+57+58+60)=55\dfrac{1}{8}(50+52+53+54+56+57+58+60)=55


Variance of population 


σ2=Σ(xixˉ)2n=18(25+9+4+1\sigma^2=\dfrac{\Sigma(x_i-\bar{x})^2}{n}=\dfrac{1}{8}(25+9+4+1+1+4+9+25)=788=9.75+1+4+9+25)=\dfrac{78}{8}=9.75


σ=9.753.1225\sigma=\sqrt{9.75}\approx3.1225

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=8C2=28.^{N}C_n=^{8}C_2=28.

noSampleSamplemean (xˉ)150,52102/2250,53103/2350,54104/2450,56106/2550,57107/2650,58108/2750,60110/2852,53105/2952,54106/21052,56108/21152,57109/21252,58110/21352,60112/21453,54107/21553,56109/21653,57110/21753,58111/21853,60113/21954,56110/22054,57111/22154,58112/22254,60114/22356,57113/22456,58114/22556,60116/22657,58115/22757,60117/22858,60118/2\def\arraystretch{1.5} \begin{array}{c:c:c:c:c} no & Sample & Sample \\ & & mean\ (\bar{x}) \\ \hline 1 & 50,52 & 102/2 \\ \hdashline 2 & 50,53 & 103/2 \\ \hdashline 3 & 50,54 & 104/2 \\ \hdashline 4 & 50,56 & 106/2 \\ \hdashline 5 & 50,57 & 107/2 \\ \hdashline 6 & 50,58 & 108/2 \\ \hdashline 7 & 50,60 & 110/2 \\ \hdashline 8 & 52,53 & 105/2 \\ \hdashline 9 & 52,54 & 106/2 \\ \hdashline 10 & 52,56 & 108/2 \\ \hdashline 11 & 52,57 & 109/2 \\ \hdashline 12 & 52,58 & 110/2 \\ \hdashline 13 & 52,60 & 112/2 \\ \hdashline 14 & 53,54 & 107/2 \\ \hdashline 15 & 53,56 & 109/2 \\ \hdashline 16 & 53,57 & 110/2 \\ \hdashline 17 & 53,58 & 111/2 \\ \hdashline 18 & 53,60 & 113/2 \\ \hdashline 19 & 54,56 & 110/2 \\ \hdashline 20 & 54,57 & 111/2 \\ \hdashline 21 & 54,58 & 112/2 \\ \hdashline 22 & 54,60 & 114/2 \\ \hdashline 23 & 56,57 & 113/2 \\ \hdashline 24 & 56,58 & 114/2 \\ \hdashline 25 & 56,60 & 116/2 \\ \hdashline 26 & 57,58 & 115/2 \\ \hdashline 27 & 57,60 & 117/2 \\ \hdashline 28 & 58,60 & 118/2 \\ \hdashline \end{array}






Xˉf(Xˉ)Xˉf(Xˉ)Xˉ2f(Xˉ)102/21/28102/5610404/112103/21/28103/5610609/112104/21/28104/5610816/112105/21/28105/5611025/112106/22/28212/5622472/112107/22/28214/5622898/112108/22/28216/5623328/112109/22/28218/5623762/112110/24/28440/5648400/112111/22/28222/5624642/112112/22/28224/5625088/112113/22/28226/5625538/112114/22/28228/5625992/112115/21/28115/5613225/112116/21/28116/5613456/112117/21/28117/5613689/112118/21/28118/5613924/112\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 102/2 & 1/28 & 102/56 & 10404/112 \\ \hdashline 103/2 & 1/28 & 103/56 & 10609/112 \\ \hdashline 104/2 & 1/28 & 104/56 & 10816/112 \\ \hdashline 105/2 & 1/28 & 105/56 & 11025/112 \\ \hdashline 106/2 & 2/28 & 212/56& 22472/112 \\ \hdashline 107/2 & 2/28 & 214/56 & 22898/112 \\ \hdashline 108/2 & 2/28 & 216/56 & 23328/112 \\ \hdashline 109/2 & 2/28 & 218/56 & 23762/112 \\ \hdashline 110/2 & 4/28 & 440/56 & 48400/112 \\ \hdashline 111/2 & 2/28 & 222/56 & 24642/112 \\ \hdashline 112/2 & 2/28 & 224/56 & 25088/112 \\ \hdashline 113/2 & 2/28 & 226/56 & 25538/112 \\ \hdashline 114/2 & 2/28 & 228/56 & 25992/112 \\ \hdashline 115/2 & 1/28 & 115/56 & 13225/112 \\ \hdashline 116/2 & 1/28 & 116/56 & 13456/112 \\ \hdashline 117/2 & 1/28 & 117/56 & 13689/112 \\ \hdashline 118/2 & 1/28 & 118/56 & 13924/112 \\ \hdashline \end{array}



Mean of sampling distribution 




μXˉ=E(Xˉ)=Xˉif(Xˉi)=308056=55=μ\mu_{\bar{X}}=E(\bar{X})=\sum\bar{X}_if(\bar{X}_i)=\dfrac{3080}{56}=55=\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=339268112(55)2=11728=σ2n(NnN1)=\dfrac{339268}{112}-(55)^2=\dfrac{117}{28}= \dfrac{\sigma^2}{n}(\dfrac{N-n}{N-1})σXˉ=σXˉ2=117282.044\sigma_{\bar{X}}=\sqrt{\sigma^2_{\bar{X}}}=\sqrt{\dfrac{117}{28}}\approx2.044


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