Question #305847

consider a population consisting of 2,5,8,11,13 and 25. suppose sample of size 5 are drawn from this population.

1
Expert's answer
2022-03-07T04:16:04-0500

We have population values 2,5,8,11,13,252,5,8,11,13,25 population size N=6N=6 and sample size n=5.n=5.

Thus, the number of possible samples which can be drawn without replacements is (65)=6.\dbinom{6}{5}=6.

1.


mean=μ=2+5+8+11+13+256=323mean=\mu=\dfrac{2+5+8+11+13+25}{6}=\dfrac{32}{3}

2


Variance=σ2=16((2323)2+(5323)2Variance=\sigma^2=\dfrac{1}{6}((2-\dfrac{32}{3})^2+(5-\dfrac{32}{3})^2




+(8323)2+(11323)2+(13323)2+(8-\dfrac{32}{3})^2+(11-\dfrac{32}{3})^2+(13-\dfrac{32}{3})^2




+(25323)2)=4889+(25-\dfrac{32}{3})^2)=\dfrac{488}{9}σ=σ2=4889=212237.363574\sigma=\sqrt{\sigma^2}=\sqrt{\dfrac{488}{9}}=\dfrac{2\sqrt{122}}{3}\approx7.363574



3.


Sample valuesSample mean (xˉ)2,5,8,11,137.82,5,8,11,2510.22,5,8,13,2510.62,5,11,13,2511.22,8,11,13,2511.85,8,11,13,2512.4\def\arraystretch{1.5} \begin{array}{c:c} Sample\ values & Sample\ mean\ (\bar{x}) \\ \hline 2,5,8,11,13 & 7.8 \\ \hdashline 2,5,8,11,25 & 10.2 \\ \hdashline 2,5,8,13,25 & 10.6 \\ \hdashline 2,5,11,13,25 & 11.2\\ \hdashline 2,8,11,13,25 & 11.8 \\ \hdashline 5,8,11,13,25 & 12.4 \\ \hdashline \end{array}



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


xˉff(xˉ)xˉf(xˉ)xˉ2f(xˉ)7.811/67.8/660.84/610.211/610.2/6104.04/610.611/610.6/6112.36/611.211/611.2/6125.44/611.811/611.8/6139.24/612.411/612.4/6153.76/6Sum=6132/3695.68/6\def\arraystretch{1.5} \begin{array}{c:c:c:c:c:c} & \bar{x} & f & f(\bar{x}) & \bar{x}f(\bar{x}) & \bar{x}^2f(\bar{x})\\ \hline & 7.8 & 1 & 1/6 & 7.8/6 & 60.84/6 \\ \hdashline & 10.2 & 1 & 1/6 & 10.2/6 & 104.04/6 \\ \hdashline & 10.6 & 1 & 1/6 & 10.6/6 & 112.36/6 \\ \hdashline & 11.2 & 1 & 1/6 & 11.2/6 & 125.44/6 \\ \hdashline & 11.8 & 1 & 1/6 & 11.8/6 & 139.24/6 \\ \hdashline & 12.4 & 1 & 1/6 & 12.4/6 & 153.76/6 \\ \hdashline Sum= & & 6 & 1 & 32/3 & 695.68/6 \\ \hdashline \end{array}


6.


μXˉ=E(Xˉ)=xˉf(xˉ)=323\mu_{\bar{X}}=E(\bar{X})=\sum\bar{x}f(\bar{x})=\dfrac{32}{3}



7.


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




=347.843(323)2=19.529=\dfrac{347.84}{3}-(\dfrac{32}{3})^2=\dfrac{19.52}{9}




σXˉ=σXˉ2=19.5291.472715\sigma_{\bar{X}}=\sqrt{\sigma_{\bar{X}}^2}=\sqrt{\dfrac{19.52}{9}}\approx1.472715



Check


μXˉ=E(Xˉ)=323=μ\mu_{\bar{X}}=E(\bar{X})=\dfrac{32}{3}=\mu




Var(Xˉ)=19.529=σ2nNnN1=4889(5)6561Var(\bar{X})=\dfrac{19.52}{9}=\dfrac{\sigma^2}{n}\cdot\dfrac{N-n}{N-1}=\dfrac{488}{9(5)}\cdot\dfrac{6-5}{6-1}




Need a fast expert's response?

Submit order

and get a quick answer at the best price

for any assignment or question with DETAILED EXPLANATIONS!

Comments

No comments. Be the first!
LATEST TUTORIALS
APPROVED BY CLIENTS