We have population values 6,9,15,18, 6 , 9 , 15 , 18 , population size N=4 N = 4
\mu=\dfrac{6+9+15+18}{4}=12 μ = 4 6 + 9 + 15 + 18 = 12 \sigma^2=\dfrac{1}{4}((6-12)^2+(9-12)^2+(15-12)^2 σ 2 = 4 1 (( 6 − 12 ) 2 + ( 9 − 12 ) 2 + ( 15 − 12 ) 2 +(18-12)^2)=\dfrac{45}{2} + ( 18 − 12 ) 2 ) = 2 45
\sigma=\sqrt{\sigma^2}=\sqrt{\dfrac{45}{2}}=3\sqrt{2.5}\approx4.7434 σ = σ 2 = 2 45 = 3 2.5 ≈ 4.7434
Sample size is n=2. n = 2. Thus, the number of possible samples which can be drawn without replacement is
\dbinom{N}{n}=\dbinom{4}{2}=6 ( n N ) = ( 2 4 ) = 6 \def\arraystretch{1.5} \begin{array}{c:c:c} Sample & Sample & Sample \ mean \\ No. & values & (\bar{X}) \\ \hline 1 & 6,9 & 7.5 \\ \hdashline 2 & 6,15 & 10.5 \\ \hdashline 3 & 6,18 & 12 \\ \hdashline 4 & 9,15 & 12 \\ \hdashline 5 & 9,18 & 13.5 \\ \hdashline 6 & 15,18 & 16.5 \\ \hline \end{array} S am pl e N o . 1 2 3 4 5 6 S am pl e v a l u es 6 , 9 6 , 15 6 , 18 9 , 15 9 , 18 15 , 18 S am pl e m e an ( X ˉ ) 7.5 10.5 12 12 13.5 16.5
The sampling distribution of the sample means.
\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 & 7.5 & 1 & 1/6 & 15/12 & 75/8\\ \hdashline & 10.5 & 1& 1/6 & 21/12 & 147/8 \\ \hdashline & 12 & 2 & 1/3 & 4 & 48 \\ \hdashline & 13.5 & 1& 1/6 & 27/12 & 243/8 \\ \hdashline & 16.5 & 1 & 1/6 & 33/12 & 363/8\\ \hdashline Total & & 6 & 1 & 12 & 303/2 \\ \hline \end{array} T o t a l X ˉ 7.5 10.5 12 13.5 16.5 f 1 1 2 1 1 6 f ( X ˉ ) 1/6 1/6 1/3 1/6 1/6 1 X ˉ f ( X ˉ ) 15/12 21/12 4 27/12 33/12 12 X ˉ 2 f ( X ˉ ) 75/8 147/8 48 243/8 363/8 303/2
E(\bar{X})=\sum\bar{X}f(\bar{X})=12 E ( X ˉ ) = ∑ X ˉ f ( X ˉ ) = 12
The mean of the sampling distribution of the sample means is equal to the the mean of the population.
E(\bar{X})=\mu_{\bar{X}}=12=\mu E ( X ˉ ) = μ X ˉ = 12 = μ
Var(\bar{X})=\sum\bar{X}^2f(\bar{X})-(\sum\bar{X}f(\bar{X}))^2 Va r ( X ˉ ) = ∑ X ˉ 2 f ( X ˉ ) − ( ∑ X ˉ f ( X ˉ ) ) 2
=\dfrac{303}{2}-(12)^2=\dfrac{15}{2} = 2 303 − ( 12 ) 2 = 2 15
\sigma_{\bar{X}}=\sqrt{Var(\bar{X})}=\sqrt{\dfrac{15}{2}}\approx2.7386 σ X ˉ = Va r ( X ˉ ) = 2 15 ≈ 2.7386
Verification:
Var(\bar{X})=\dfrac{\sigma^2}{n}(\dfrac{N-n}{N-1})=\dfrac{45}{2(2)}(\dfrac{4-2}{4-1}) Va r ( X ˉ ) = n σ 2 ( N − 1 N − n ) = 2 ( 2 ) 45 ( 4 − 1 4 − 2 ) =\dfrac{15}{2}, True = 2 15 , T r u e