Question #241175

Draw all possible samples of size 2 with replacement from population :  2  4   6  8   10.

prove that population mean is same as samples mean.


1
Expert's answer
2021-09-27T07:39:00-0400

In total there are 52=255^2=25 samples or pairs which are possible

SampleMeanSampleMean(2,2)2(2,4)3(2,6)4(2,8)5(2,10)6(4,2)3(4,4)4(4,6)5(4,8)6(4,10)7(6,2)4(6,4)5(6,6)6(6,8)7(6,10)8(8,2)5(8,4)6(8,6)7(8,8)8(8,10)9(10,2)6(10,4)7(10,6)8(10,8)9(10,10)10\def\arraystretch{1.5} \begin{array}{c:c:c:c:c:} Sample & Mean & & Sample & Mean & & \\ \hline (2,2) & 2 & & (2,4) & 3 \\ \hdashline (2,6) & 4 & & (2,8) & 5 \\ \hdashline (2,10) & 6 & & (4,2) & 3 \\ \hdashline (4,4) & 4 & & (4,6) & 5 \\ \hdashline (4,8) & 6 & & (4,10) & 7 \\ \hdashline (6,2) & 4 & & (6,4) & 5 \\ \hdashline (6,6) & 6 & & (6,8) & 7 \\ \hdashline (6,10) & 8 & & (8,2) & 5 \\ \hdashline (8,4) & 6 & & (8,6) & 7 \\ \hdashline (8,8) & 8 & & (8,10) & 9 \\ \hdashline (10,2) & 6 & & (10,4) & 7 \\ \hdashline (10,6) & 8 & & (10,8) & 9 \\ \hdashline (10,10) & 10 & & \\ \end{array}

The table shows that there are nine possible values of the sample mean Xˉ.\bar{X}.


xˉp(xˉ)21/2532/2543/2554/2565/2574/2583/2592/25101/25\def\arraystretch{1.5} \begin{array}{c:c} \bar{x} & p(\bar{x}) \\ \hline 2 & 1/25 \\ 3 & 2/25 \\ 4 & 3/25 \\ 5 & 4/25 \\ 6 & 5/25 \\ 7 & 4/25 \\ 8 & 3/25 \\ 9 & 2/25 \\ 10 & 1/25 \\ \end{array}

μXˉ=ixˉip(xˉi)=2(125)+3(225)+4(325)\mu_{\bar{X}}=\sum_i\bar{x}_ip(\bar{x}_i)=2(\dfrac{1}{25})+3(\dfrac{2}{25})+4(\dfrac{3}{25})

+5(425)+6(525)+7(425)+8(325)+9(225)+5(\dfrac{4}{25})+6(\dfrac{5}{25})+7(\dfrac{4}{25})+8(\dfrac{3}{25})+9(\dfrac{2}{25})

+10(125)=6+10(\dfrac{1}{25})=6

ixˉi2p(xˉi)=(2)2(125)+(3)2(225)+(4)2(325)\sum_i\bar{x}_i^2p(\bar{x}_i)=(2)^2(\dfrac{1}{25})+(3)^2(\dfrac{2}{25})+(4)^2(\dfrac{3}{25})

+(5)2(425)+(6)2(525)+(7)2(425)+(8)2(325)+(5)^2(\dfrac{4}{25})+(6)^2(\dfrac{5}{25})+(7)^2(\dfrac{4}{25})+(8)^2(\dfrac{3}{25})

+(9)2(225)+(10)2(125)=40+(9)^2(\dfrac{2}{25})+(10)^2(\dfrac{1}{25})=40

Var(Xˉ)=σXˉ2=ixˉi2p(xˉi)(ixˉip(xˉi))2Var(\bar{X})=\sigma_{\bar{X}}^2=\sum_i\bar{x}_i^2p(\bar{x}_i)-(\sum_i\bar{x}_ip(\bar{x}_i))^2

=40(6)2=4=40-(6)^2=4

σXˉ=σXˉ2=100=10\sigma_{\bar{X}}=\sqrt{\sigma_{\bar{X}}^2}=\sqrt{100}=10

μ=2+4+6+8+105=6\mu=\dfrac{2+4+6+8+10}{5}=6

In sampling with replacement the mean of all sample means equals the mean of the population:

μXˉ=6=μ\mu_{\bar{X}}=6=\mu

σ2=15((26)2+(46)2+(66)2\sigma^2=\dfrac{1}{5}((2-6)^2+(4-6)^2+(6-6)^2

+(86)2+(106)2)=8+(8-6)^2+(10-6)^2)=8

When sampling with replacement the variation of all sample means equals the variation of the population divided by the sample size 


σXˉ2=σ2n\sigma_{\bar{X}}^2=\dfrac{\sigma^2}{n}

4=824=\dfrac{8}{2}


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