Question #341338

A population consists of six values (6, 9, 12, 15, 18, and 21). (with illustration)

e. Determine the mean, variance and standard deviation of the sample mean.


Expert's answer

We have population values 6,9,12,15,21, population size N=5 and sample size n=3.

Mean of population (μ)(\mu) = 6+9+12+15+215=12.6\dfrac{6+9+12+15+21}{5}=12.6

Variance of population 


σ2=Σ(xixˉ)2n=15(43.56+12.96+0.36\sigma^2=\dfrac{\Sigma(x_i-\bar{x})^2}{n}=\dfrac{1}{5}(43.56+12.96+0.36


+5.76+70.56)=26.64+5.76+70.56)=26.64

σ=σ2=26.645.1614\sigma=\sqrt{\sigma^2}=\sqrt{26.64}\approx5.1614

A. 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 NCn=5C3=10.^{N}C_n=^{5}C_3=10.

noSampleSamplemean (xˉ)16,9,12926,9,151036,9,211246,12,151156,12,211366,15,211479,12,151289,12,211499,15,21151012,15,2116\def\arraystretch{1.5} \begin{array}{c:c:c:c:c} no & Sample & Sample \\ & & mean\ (\bar{x}) \\ \hline 1 & 6,9,12 & 9 \\ \hdashline 2 & 6,9,15 & 10 \\ \hdashline 3 & 6,9,21 & 12 \\ \hdashline 4 & 6,12,15 & 11 \\ \hdashline 5 & 6,12,21 & 13 \\ \hdashline 6 & 6,15,21 & 14 \\ \hdashline 7 & 9,12,15 & 12 \\ \hdashline 8 & 9,12,21 & 14 \\ \hdashline 9 & 9,15,21 & 15 \\ \hdashline 10 & 12,15,21 & 16 \\ \hdashline \end{array}



B.


Xˉf(Xˉ)Xˉf(Xˉ)Xˉ2f(Xˉ)91/109/1081/10101/1010/10100/10111/1011/10121/10122/1024/10288/10131/1013/10169/10142/1028/10392/10151/1015/10225/10161/1016/10256/10\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 9 & 1/10 & 9/10 & 81/10 \\ \hdashline 10 & 1/10 & 10/10 & 100/10 \\ \hdashline 11 & 1/10 & 11/10 & 121/10 \\ \hdashline 12 & 2/10 & 24/10 & 288/10 \\ \hdashline 13 & 1/10 & 13/10 & 169/10 \\ \hdashline 14 & 2/10 & 28/10 & 392/10 \\ \hdashline 15 & 1/10 & 15/10 & 225/10 \\ \hdashline 16 & 1/10 & 16/10 & 256/10 \\ \hdashline \end{array}



Mean of sampling distribution 

μXˉ=E(Xˉ)=Xˉif(Xˉi)=12610=12.6=μ\mu_{\bar{X}}=E(\bar{X})=\sum\bar{X}_if(\bar{X}_i)=\dfrac{126}{10}=12.6=\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=163210(12.6)2=4.44=σ2n(NnN1)=\dfrac{1632}{10}-(12.6)^2=4.44= \dfrac{\sigma^2}{n}(\dfrac{N-n}{N-1})

σXˉ=4.442.1071\sigma_{\bar{X}}=\sqrt{4.44}\approx2.1071


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