We have population values 2,4,6,8 2 , 4 , 6 , 8 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 4^2=16. 4 2 = 16.
a.
\def\arraystretch{1.5} \begin{array}{c:c} Sample\ values & Sample\ mean(\bar{X}) \\ \hline 2,2 & 2\\ \hdashline 2,4 & 3\\ \hdashline 2,6 & 4\\ \hdashline 2,8 & 5\\ \hdashline 4,2 & 3\\ \hdashline 4,4 & 4\\ \hdashline 4,6 & 5\\ \hdashline 4,8 & 6\\ \hdashline 6,2 & 4\\ \hdashline 6,4 & 5\\ \hdashline 6,6 & 6\\ \hdashline 6,8 & 7\\ \hdashline 8,2 & 5\\ \hdashline 8,4 & 6\\ \hdashline 8,6 & 7\\ \hdashline 8,8 & 8\\ \hdashline \end{array} S am pl e v a l u es 2 , 2 2 , 4 2 , 6 2 , 8 4 , 2 4 , 4 4 , 6 4 , 8 6 , 2 6 , 4 6 , 6 6 , 8 8 , 2 8 , 4 8 , 6 8 , 8 S am pl e m e an ( X ˉ ) 2 3 4 5 3 4 5 6 4 5 6 7 5 6 7 8
b.The sampling distribution of the sample mean \bar{X} X ˉ is
\def\arraystretch{1.5} \begin{array}{c:c:c:c:c:c:c} & \bar{X} & f & f(\bar{X}) & Xf(\bar{X})& X^2f(\bar{X}) \\ \hline & 2 & 1 & 1/16 & 2/16 & 4/16\\ \hdashline & 3 & 2 & 2/16 & 6/16 & 18/16 \\ \hdashline & 4 & 3 & 3/16 & 12/16 & 48/16\\ \hdashline & 5 & 4 & 4/16 & 20/16 & 100/16 \\ \hdashline & 6 & 3 & 3/16 & 18/16 & 108/16 \\ \hdashline & 7 & 2 & 2/16 & 14/16 & 98/16 \\ \hdashline & 8 & 1 & 1/16 & 8/16 & 64/16\\ \hdashline Sum= & & 16 & 1 & 5 & 55/2\\ \hdashline \end{array} S u m = X ˉ 2 3 4 5 6 7 8 f 1 2 3 4 3 2 1 16 f ( X ˉ ) 1/16 2/16 3/16 4/16 3/16 2/16 1/16 1 X f ( X ˉ ) 2/16 6/16 12/16 20/16 18/16 14/16 8/16 5 X 2 f ( X ˉ ) 4/16 18/16 48/16 100/16 108/16 98/16 64/16 55/2
c.
\mu=\dfrac{2+4+6+8}{4}=5 μ = 4 2 + 4 + 6 + 8 = 5
\sigma^2=\dfrac{1}{4}((2-5)^2+(4-5)^2+(6-5)^2+(8-5)^2) σ 2 = 4 1 (( 2 − 5 ) 2 + ( 4 − 5 ) 2 + ( 6 − 5 ) 2 + ( 8 − 5 ) 2 )
=5 = 5
Check
The mean of the sample means is
\mu_{\bar{X}}=E(\bar{X})=5=\mu μ X ˉ = E ( X ˉ ) = 5 = μ
Var(\bar{X})=\sigma^2_{\bar{X}}=E(\bar{X}^2)-(E(\bar{X}))^2 Va r ( X ˉ ) = σ X ˉ 2 = E ( X ˉ 2 ) − ( E ( X ˉ ) ) 2
=\dfrac{55}{2}-(5)^2=\dfrac{5}{2} = 2 55 − ( 5 ) 2 = 2 5
The standard deviation of the sample means is
\sigma_{\bar{X}}=\sqrt{\sigma^2_{\bar{X}}}=\sqrt{5/2} σ X ˉ = σ X ˉ 2 = 5/2
\dfrac{\sigma^2}{n}=\dfrac{5}{2}=\sigma^2_{\bar{X}} n σ 2 = 2 5 = σ X ˉ 2
\mu_{\bar{X}}=\mu μ X ˉ = μ
\sigma_{\bar{X}}=\dfrac{\sigma}{\sqrt{n}} σ X ˉ = n σ