1. We have population values 6,9,12,15,17, population size N=5 and sample size n=3.
Mean of population ( μ ) (\mu) ( μ ) = 6 + 9 + 12 + 15 + 17 5 = 11.8 \dfrac{6+9+12+15+17}{5}=11.8 5 6 + 9 + 12 + 15 + 17 = 11.8
Variance of population
σ 2 = Σ ( x i − x ˉ ) 2 n = 1 5 ( 33.64 + 7.84 + 0.04 \sigma^2=\dfrac{\Sigma(x_i-\bar{x})^2}{n}=\dfrac{1}{5}(33.64+7.84+0.04 σ 2 = n Σ ( x i − x ˉ ) 2 = 5 1 ( 33.64 + 7.84 + 0.04
+ 10.24 + 27.04 ) = 15.76 +10.24+27.04)=15.76 + 10.24 + 27.04 ) = 15.76
σ = σ 2 = 15.76 ≈ 3.9699 \sigma=\sqrt{\sigma^2}=\sqrt{15.76}\approx3.9699 σ = σ 2 = 15.76 ≈ 3.9699
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 6 , 9 , 12 27 / 3 2 6 , 9 , 15 30 / 3 3 6 , 9 , 17 32 / 3 4 6 , 12 , 15 33 / 3 5 6 , 12 , 17 35 / 3 6 6 , 15 , 17 38 / 3 7 9 , 12 , 15 36 / 3 8 9 , 12 , 17 38 / 3 9 9 , 15 , 17 41 / 3 10 12 , 15 , 17 44 / 3 \def\arraystretch{1.5}
\begin{array}{c:c:c:c:c}
no & Sample & Sample \\
& & mean\ (\bar{x})
\\ \hline
1 & 6,9,12 & 27/3 \\
\hdashline
2 & 6,9,15 & 30/3 \\
\hdashline
3 & 6,9,17 & 32/3 \\
\hdashline
4 & 6,12,15 & 33/3 \\
\hdashline
5 & 6,12,17 & 35/3 \\
\hdashline
6 & 6,15,17 & 38/3 \\
\hdashline
7 & 9,12,15 & 36/3 \\
\hdashline
8 & 9,12,17& 38/3 \\
\hdashline
9 & 9,15,17 & 41/3 \\
\hdashline
10 & 12,15,17 & 44/3 \\
\hdashline
\end{array} n o 1 2 3 4 5 6 7 8 9 10 S am pl e 6 , 9 , 12 6 , 9 , 15 6 , 9 , 17 6 , 12 , 15 6 , 12 , 17 6 , 15 , 17 9 , 12 , 15 9 , 12 , 17 9 , 15 , 17 12 , 15 , 17 S am pl e m e an ( x ˉ ) 27/3 30/3 32/3 33/3 35/3 38/3 36/3 38/3 41/3 44/3
X ˉ f ( X ˉ ) X ˉ f ( X ˉ ) X ˉ 2 f ( X ˉ ) 27 / 3 1 / 10 27 / 30 729 / 90 30 / 3 1 / 10 30 / 30 900 / 90 32 / 3 1 / 10 32 / 30 1024 / 90 33 / 3 1 / 10 33 / 30 1089 / 90 35 / 3 1 / 10 35 / 30 1225 / 90 36 / 3 1 / 10 36 / 30 1296 / 90 38 / 3 2 / 10 76 / 30 2888 / 90 41 / 3 1 / 10 41 / 30 1681 / 90 44 / 3 1 / 10 44 / 30 1936 / 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
27/3 & 1/10 & 27/30 & 729/90 \\
\hdashline
30/3 & 1/10& 30/30 & 900/90 \\
\hdashline
32/3 & 1/10 & 32/30 & 1024/90 \\
\hdashline
33/3 & 1/10 & 33/30 & 1089/90 \\
\hdashline
35/3 & 1/10 & 35/30 & 1225/90 \\
\hdashline
36/3 & 1/10 & 36/30 & 1296/90 \\
\hdashline
38/3 & 2/10 & 76/30 & 2888/90 \\
\hdashline
41/3 & 1/10 & 41/30 & 1681/90 \\
\hdashline
44/3 & 1/10 & 44/30 & 1936/90 \\
\hdashline
\end{array} X ˉ 27/3 30/3 32/3 33/3 35/3 36/3 38/3 41/3 44/3 f ( X ˉ ) 1/10 1/10 1/10 1/10 1/10 1/10 2/10 1/10 1/10 X ˉ f ( X ˉ ) 27/30 30/30 32/30 33/30 35/30 36/30 76/30 41/30 44/30 X ˉ 2 f ( X ˉ ) 729/90 900/90 1024/90 1089/90 1225/90 1296/90 2888/90 1681/90 1936/90
Mean of sampling distribution
μ X ˉ = E ( X ˉ ) = ∑ X ˉ i f ( X ˉ i ) = 11.8 = μ \mu_{\bar{X}}=E(\bar{X})=\sum\bar{X}_if(\bar{X}_i)=11.8=\mu μ X ˉ = E ( X ˉ ) = ∑ X ˉ i f ( X ˉ i ) = 11.8 = 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 = 12768 90 − ( 11.8 ) 2 = 7.88 3 = σ 2 n ( N − n N − 1 ) =\dfrac{12768}{90}-(11.8)^2=\dfrac{7.88}{3}= \dfrac{\sigma^2}{n}(\dfrac{N-n}{N-1}) = 90 12768 − ( 11.8 ) 2 = 3 7.88 = n σ 2 ( N − 1 N − n )
σ X ˉ = 7.88 3 ≈ 1.6207 \sigma_{\bar{X}}=\sqrt{\dfrac{7.88}{3}}\approx1.6207 σ X ˉ = 3 7.88 ≈ 1.6207
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