Question #304216

A population consists of the four numbers 1, 2, and 4. List all the possible samples of size n=2 which can be drawn replacement from the population. Find the following



a.) Population means


b.) Population Variance


c.) Population Standard Deviation


d.) Mean of the sampling distribution of sample means


e.) Variance of the sampling distribution of sample means


f.) Standard deviation of the sampling distribution of sample means

1
Expert's answer
2022-03-01T18:39:39-0500

We have population values 1,2,4,51,2,4,5 population size N=4,N=4, and sample size n=2.n=2. Thus, the number of possible samples which can be drawn with replacement is 42=16.4^2=16.

a)



mean=μ=1+2+4+54=3mean=\mu=\dfrac{1+2+4+5}{4}=3

b)


Variance=σ2=14((13)2+(23)2Variance=\sigma^2=\dfrac{1}{4}((1-3)^2+(2-3)^2




+(43)2+(53)2)=2.5+(4-3)^2+(5-3)^2)=2.5

c)



σ=σ21.581139\sigma=\sqrt{\sigma^2}\approx1.581139

d)


NoSampleMean1(1,1)12(1,2)1.53(1,4)2.54(1,5)35(2,1)1.56(2,2)27(2,4)38(2,5)3.59(4,1)2.510(4,2)311(4,4)412(4,5)4.513(5,1)314(5,2)3.515(5,4)4.516(5,5)5\def\arraystretch{1.5} \begin{array}{c:c:c} No & Sample & Mean \\ \hline 1 & (1,1) & 1 \\ \hdashline 2 & (1,2) & 1.5 \\ \hdashline 3 & (1,4) & 2.5 \\ \hdashline 4 & (1,5) & 3 \\ \hdashline 5 & (2,1) & 1.5 \\ \hdashline 6 & (2,2) & 2 \\ \hdashline 7 & (2,4) & 3 \\ \hdashline 8 & (2,5) & 3.5 \\ \hdashline 9 & (4,1) & 2.5 \\ \hdashline 10 & (4,2) & 3 \\ \hdashline 11 & (4,4) & 4 \\ \hdashline 12 & (4,5) & 4.5 \\ \hdashline 13 & (5,1) & 3 \\ \hdashline 14 & (5,2) & 3.5 \\ \hdashline 15 & (5,4) &4.5 \\ \hdashline 16 & (5,5) & 5 \\ \hdashline \end{array}


The sampling distribution of the sample mean xˉ\bar{x} and its mean and standard deviation are:


xˉff(xˉ)xˉf(xˉ)xˉ2f(xˉ)111/161/162/321.522/163/169/32211/162/168/322.522/165/1625/32344/1612/1672/323.522/167/1649/32411/164/1632/324.522/169/1681/32511/165/1650/32Total161341/4\def\arraystretch{1.5} \begin{array}{c:c:c:c:c:} \bar{x} & f & f(\bar{x})& \bar{x}f(\bar{x})& \bar{x}^2f(\bar{x}) \\ \hline 1& 1 & 1/16 & 1/16 & 2/32 \\ \hdashline 1.5 & 2 & 2/16 & 3/16 & 9/32 \\ \hdashline 2 & 1 & 1/16 & 2/16 & 8/32 \\ \hdashline 2.5 & 2 & 2/16 & 5/16 & 25/32 \\ \hdashline 3 & 4 & 4/16 & 12/16 & 72/32 \\ \hdashline 3.5 & 2 & 2/16 & 7/16 & 49/32 \\ \hdashline 4 & 1 & 1/16 & 4/16 & 32/32 \\ \hdashline 4.5 & 2 & 2/16 & 9/16 & 81/32 \\ \hdashline 5 & 1 & 1/16 & 5/16 & 50/32 \\ \hdashline Total & 16 & 1 & 3 & 41/4 \\ \hdashline \end{array}




μXˉ=E(Xˉ)=xˉf(xˉ)=5\mu_{\bar{X}}=E(\bar{X})=\sum\bar{x}f(\bar{x})=5

e)


Var(Xˉ)=σXˉ2=xˉ2f(xˉ)(xˉf(xˉ))2Var(\bar{X})=\sigma_{\bar{X}}^2=\sum\bar{x}^2f(\bar{x})-(\sum\bar{x}f(\bar{x}))^2=41432=54=\dfrac{41}{4}-3^2=\dfrac{5}{4}

f)



σXˉ=σXˉ2=54=521.118034\sigma_{\bar{X}}=\sqrt{\sigma_{\bar{X}}^2}=\sqrt{\dfrac{5}{4}}=\dfrac{\sqrt{5}}{2}\approx1.118034



Check


μXˉ=E(Xˉ)=5=μ\mu_{\bar{X}}=E(\bar{X})=5=\mu




Var(Xˉ)=54=σ2n=2.52Var(\bar{X})=\dfrac{5}{4}=\dfrac{\sigma^2}{n}=\dfrac{2.5}{2}




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