We have population values 1,5,8 population size N=3 and sample size n=2.
1.Population mean
μ = 1 + 5 + 8 3 = 14 3 \mu=\dfrac{1+5+8}{3}=\dfrac{14}{3} μ = 3 1 + 5 + 8 = 3 14
2. Population variance
σ 2 = Σ ( x i − x ˉ ) 2 n = 121 9 + 1 9 + 100 9 3 = 74 9 \sigma^2=\dfrac{\Sigma(x_i-\bar{x})^2}{n}=\dfrac{\dfrac{121}{9}+\dfrac{1}{9}+\dfrac{100}{9}}{3}=\dfrac{74}{9} σ 2 = n Σ ( x i − x ˉ ) 2 = 3 9 121 + 9 1 + 9 100 = 9 74
3. Population standard deviation
σ = σ 2 = 74 9 = 74 3 ≈ 2.867442 \sigma=\sqrt{\sigma^2}=\sqrt{\dfrac{74}{9}}=\dfrac{\sqrt{74}}{3}\approx2.867442 σ = σ 2 = 9 74 = 3 74 ≈ 2.867442
4. The number of possible samples which can be drawn with replacement is N n = 3 2 = 9. N^n=3^2=9. N n = 3 2 = 9.
n o S a m p l e S a m p l e m e a n ( x ˉ ) 1 1 , 1 2 / 2 2 1 , 5 6 / 2 3 1 , 8 9 / 2 4 5 , 1 6 / 2 5 5 , 5 10 / 2 6 5 , 8 13 / 2 7 8 , 1 9 / 2 8 8 , 5 13 / 2 9 8 , 8 16 / 2 \def\arraystretch{1.5}
\begin{array}{c:c:c:c:c}
no & Sample & Sample \\
& & mean\ (\bar{x})
\\ \hline
1 & 1,1 & 2/2 \\
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2 & 1,5 & 6/2 \\
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3 & 1,8 & 9/2 \\
\hdashline
4 & 5,1 & 6/2 \\
\hdashline
5 & 5,5 & 10/2 \\
\hdashline
6 & 5,8 & 13/2 \\
\hdashline
7 & 8,1 & 9/2 \\
\hdashline
8 & 8,5 & 13/2 \\
\hdashline
9 & 8,8 & 16/2 \\
\hdashline
\end{array} n o 1 2 3 4 5 6 7 8 9 S am pl e 1 , 1 1 , 5 1 , 8 5 , 1 5 , 5 5 , 8 8 , 1 8 , 5 8 , 8 S am pl e m e an ( x ˉ ) 2/2 6/2 9/2 6/2 10/2 13/2 9/2 13/2 16/2
X ˉ f ( X ˉ ) X ˉ f ( X ˉ ) X ˉ 2 f ( X ˉ ) 2 / 2 1 / 9 2 / 18 4 / 36 6 / 2 2 / 9 12 / 18 72 / 36 9 / 2 2 / 9 18 / 18 162 / 36 10 / 2 1 / 9 10 / 18 100 / 36 13 / 2 2 / 9 26 / 18 338 / 36 16 / 2 1 / 9 16 / 18 256 / 36 \def\arraystretch{1.5}
\begin{array}{c:c:c:c:c}
\bar{X} & f(\bar{X}) &\bar{X} f(\bar{X}) &\bar{X}^2 f(\bar{X})\\ \hline
2/2 & 1/9 & 2/18 & 4/36\\
\hdashline
6/2 & 2/9 & 12/18 & 72/36\\
\hdashline
9/2 & 2/9 & 18/18 & 162/36\\
\hdashline
10/2 & 1/9 & 10/18 & 100/36\\
\hdashline
13/2 & 2/9 & 26/18 & 338/36\\
\hdashline
16/2 & 1/9 & 16/18 & 256/36\\
\hdashline
\end{array} X ˉ 2/2 6/2 9/2 10/2 13/2 16/2 f ( X ˉ ) 1/9 2/9 2/9 1/9 2/9 1/9 X ˉ f ( X ˉ ) 2/18 12/18 18/18 10/18 26/18 16/18 X ˉ 2 f ( X ˉ ) 4/36 72/36 162/36 100/36 338/36 256/36
Mean of sampling distribution
μ X ˉ = E ( X ˉ ) = ∑ X ˉ i f ( X ˉ i ) = 14 3 = μ \mu_{\bar{X}}=E(\bar{X})=\sum\bar{X}_if(\bar{X}_i)=\dfrac{14}{3}=\mu μ X ˉ = E ( X ˉ ) = ∑ X ˉ i f ( X ˉ i ) = 3 14 = 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 = 932 36 − ( 14 3 ) 2 = 37 9 = σ 2 n =\dfrac{932}{36}-(\dfrac{14}{3})^2=\dfrac{37}{9}= \dfrac{\sigma^2}{n} = 36 932 − ( 3 14 ) 2 = 9 37 = n σ 2
The standard error of the mean
σ X ˉ = 37 9 ≈ 2.0276 \sigma_{\bar{X}}=\sqrt{\dfrac{37}{9}}\approx2.0276 σ X ˉ = 9 37 ≈ 2.0276
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