We have population values 2,4,6,8,10, population size N=5 and sample size n=3.
Mean of population ( μ ) (\mu) ( μ ) = 2 + 4 + 6 + 8 + 10 5 = 6 \dfrac{2+4+6+8+10}{5}=6 5 2 + 4 + 6 + 8 + 10 = 6
Variance of population
σ 2 = Σ ( x i − x ˉ ) 2 N = 16 + 4 + 0 + 4 + 16 5 = 8 \sigma^2=\dfrac{\Sigma(x_i-\bar{x})^2}{N}=\dfrac{16+4+0+4+16}{5}=8 σ 2 = N Σ ( x i − x ˉ ) 2 = 5 16 + 4 + 0 + 4 + 16 = 8
σ = σ 2 = 8 = 2 2 ≈ 2.8284 \sigma=\sqrt{\sigma^2}=\sqrt{8}=2\sqrt{2}\approx2.8284 σ = σ 2 = 8 = 2 2 ≈ 2.8284
a. The number of possible samples which can be drawn without replacement is N C n = 5 C 3 = 10. ^{N}C_n=^{5}C_3=10. N C n = 5 C 3 = 10.
n o S a m p l e S a m p l e m e a n ( x ˉ ) 1 2 , 4 , 6 12 / 3 2 2 , 4 , 8 14 / 3 3 2 , 4 , 10 16 / 3 4 2 , 6 , 8 16 / 3 5 2 , 6 , 10 18 / 3 6 2 , 8 , 10 20 / 3 7 4 , 6 , 8 18 / 3 8 4 , 6 , 10 20 / 3 9 4 , 8 , 10 22 / 3 10 6 , 8 , 10 24 / 3 \def\arraystretch{1.5}
\begin{array}{c:c:c:c:c}
no & Sample & Sample \\
& & mean\ (\bar{x})
\\ \hline
1 & 2,4,6 & 12/3 \\
\hdashline
2 & 2,4,8 & 14/3 \\
\hdashline
3 & 2,4,10 & 16/3\\
\hdashline
4 & 2,6,8 & 16/3 \\
\hdashline
5 & 2,6,10 & 18/3 \\
\hdashline
6 & 2,8,10 & 20/3 \\
\hdashline
7 & 4,6,8 & 18/3 \\
\hdashline
8 & 4,6,10 & 20/3 \\
\hdashline
9 & 4,8,10 & 22/3 \\
\hdashline
10 & 6,8,10 & 24/3 \\
\hdashline
\end{array} n o 1 2 3 4 5 6 7 8 9 10 S am pl e 2 , 4 , 6 2 , 4 , 8 2 , 4 , 10 2 , 6 , 8 2 , 6 , 10 2 , 8 , 10 4 , 6 , 8 4 , 6 , 10 4 , 8 , 10 6 , 8 , 10 S am pl e m e an ( x ˉ ) 12/3 14/3 16/3 16/3 18/3 20/3 18/3 20/3 22/3 24/3
X ˉ f ( X ˉ ) X ˉ f ( X ˉ ) X ˉ 2 f ( X ˉ ) 12 / 3 1 / 10 12 / 30 144 / 90 14 / 3 1 / 10 14 / 30 196 / 90 16 / 3 2 / 10 32 / 30 512 / 90 18 / 3 2 / 10 36 / 30 648 / 90 20 / 3 2 / 10 40 / 30 800 / 90 22 / 3 1 / 10 22 / 30 484 / 90 24 / 3 1 / 10 24 / 30 576 / 90 \def\arraystretch{1.5}
\begin{array}{c:c:c:c:c}
\bar{X} & f(\bar{X}) &\bar{X} f(\bar{X})& \bar{X}^2f(\bar{X})
\\ \hline
12/3 & 1/10 & 12/30 & 144/90 \\
\hdashline
14/3 & 1/10 & 14/30 & 196/90 \\
\hdashline
16/3 & 2/10 & 32/30 & 512/90 \\
\hdashline
18/3 & 2/10 & 36/30 & 648/90 \\
\hdashline
20/3 & 2/10 & 40/30 & 800/90 \\
\hdashline
22/3 & 1/10 & 22/30 & 484/90 \\
\hdashline
24/3 & 1/10 & 24/30 & 576/90 \\
\hdashline
\end{array} X ˉ 12/3 14/3 16/3 18/3 20/3 22/3 24/3 f ( X ˉ ) 1/10 1/10 2/10 2/10 2/10 1/10 1/10 X ˉ f ( X ˉ ) 12/30 14/30 32/30 36/30 40/30 22/30 24/30 X ˉ 2 f ( X ˉ ) 144/90 196/90 512/90 648/90 800/90 484/90 576/90
b. Mean of sampling distribution
μ X ˉ = E ( X ˉ ) = ∑ X ˉ i f ( X ˉ i ) = 6 = μ \mu_{\bar{X}}=E(\bar{X})=\sum\bar{X}_if(\bar{X}_i)=6=\mu μ X ˉ = E ( X ˉ ) = ∑ X ˉ i f ( X ˉ i ) = 6 = μ
The variance of sampling distribution
V a r ( X ˉ ) = σ X ˉ 2 = ∑ X ˉ i 2 f ( X ˉ i ) − [ ∑ X ˉ i f ( X ˉ i ) ] 2 Var(\bar{X})=\sigma^2_{\bar{X}}=\sum\bar{X}_i^2f(\bar{X}_i)-\big[\sum\bar{X}_if(\bar{X}_i)\big]^2 Va r ( X ˉ ) = σ X ˉ 2 = ∑ X ˉ i 2 f ( X ˉ i ) − [ ∑ X ˉ i f ( X ˉ i ) ] 2 = 3360 90 − ( 6 ) 2 = 4 3 = σ 2 n ( N − n N − 1 ) =\dfrac{3360}{90}-(6)^2=\dfrac{4}{3}= \dfrac{\sigma^2}{n}(\dfrac{N-n}{N-1}) = 90 3360 − ( 6 ) 2 = 3 4 = n σ 2 ( N − 1 N − n )
σ X ˉ = 4 3 ≈ 1.1547 \sigma_{\bar{X}}=\sqrt{\dfrac{4}{3}}\approx1.1547 σ X ˉ = 3 4 ≈ 1.1547
c.
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