We have population values 1 , 2 , 4 , 5 1,2,4,5 1 , 2 , 4 , 5 population size N = 4 N=4 N = 4 and sample size n = 3. n=3. n = 3.
Thus, the number of possible samples which can be drawn with replacement is 4 3 = 64. 4^3=64. 4 3 = 64.
a. Population mean:
μ = 1 + 2 + 4 + 5 4 = 3 \mu=\dfrac{1+2+4+5}{4}=3 μ = 4 1 + 2 + 4 + 5 = 3
b. Population variance:
σ 2 = 1 4 ( ( 1 − 3 ) 2 + ( 2 − 3 ) 2 + ( 4 − 3 ) 2 + ( 5 − 3 ) 2 ) \sigma^2=\dfrac{1}{4}((1-3)^2+(2-3)^2+(4-3)^2+(5-3)^2) σ 2 = 4 1 (( 1 − 3 ) 2 + ( 2 − 3 ) 2 + ( 4 − 3 ) 2 + ( 5 − 3 ) 2 ) = 2.5 =2.5 = 2.5
c. Population standard deviation:
σ = σ 2 = 2.5 ≈ 1.58114 \sigma=\sqrt{\sigma^2}=\sqrt{2.5}\approx1.58114 σ = σ 2 = 2.5 ≈ 1.58114
d.
S a m p l e v a l u e s S a m p l e m e a n ( X ˉ ) 1 , 1 , 1 1 1 , 1 , 2 4 / 3 1 , 1 , 4 2 1 , 1 , 5 7 / 3 1 , 2 , 1 4 / 3 1 , 2 , 2 5 / 3 1 , 2 , 4 7 / 3 1 , 2 , 5 8 / 3 1 , 4 , 1 2 1 , 4 , 2 7 / 3 1 , 4 , 4 3 1 , 4 , 5 10 / 3 1 , 5 , 1 7 / 3 1 , 5 , 2 8 / 3 1 , 5 , 4 10 / 3 1 , 5 , 5 11 / 3 2 , 1 , 1 4 / 3 2 , 1 , 2 5 / 3 2 , 1 , 4 7 / 3 2 , 1 , 5 8 / 3 2 , 2 , 1 5 / 3 2 , 2 , 2 2 2 , 2 , 4 8 / 3 2 , 2 , 5 3 2 , 4 , 1 7 / 3 2 , 4 , 2 8 / 3 2 , 4 , 4 10 / 3 2 , 4 , 5 11 / 3 2 , 5 , 1 8 / 3 2 , 5 , 2 3 2 , 5 , 4 11 / 3 2 , 5 , 5 4 4 , 1 , 1 2 4 , 1 , 2 7 / 3 4 , 1 , 4 3 4 , 1 , 5 10 / 3 4 , 2 , 1 7 / 3 4 , 2 , 2 8 / 3 4 , 2 , 4 10 / 3 4 , 2 , 5 11 / 3 4 , 4 , 1 3 4 , 4 , 2 10 / 3 4 , 4 , 4 4 4 , 4 , 5 13 / 3 4 , 5 , 1 10 / 3 4 , 5 , 2 11 / 3 4 , 5 , 4 13 / 3 4 , 5 , 5 14 / 3 5 , 1 , 1 7 / 3 5 , 1 , 2 8 / 3 5 , 1 , 4 10 / 3 5 , 1 , 5 11 / 3 5 , 2 , 1 8 / 3 5 , 2 , 2 3 5 , 2 , 4 11 / 3 5 , 2 , 5 4 5 , 4 , 1 10 / 3 5 , 4 , 2 11 / 3 5 , 4 , 4 13 / 3 5 , 4 , 5 14 / 3 5 , 5 , 1 11 / 3 5 , 5 , 2 4 5 , 5 , 4 14 / 3 5 , 5 , 5 5 \def\arraystretch{1.5}
\begin{array}{c:c}
Sample\ values & Sample\ mean(\bar{X}) \\ \hline
1,1,1 & 1\\
\hdashline
1,1,2 & 4/3\\
\hdashline
1,1,4 & 2\\
\hdashline
1,1,5 & 7/3\\
\hdashline
1,2,1 & 4/3\\
\hdashline
1,2,2 & 5/3\\
\hdashline
1,2,4 & 7/3\\
\hdashline
1,2,5 & 8/3\\
\hdashline
1,4,1 & 2\\
\hdashline
1,4,2 & 7/3\\
\hdashline
1,4,4 & 3\\
\hdashline
1,4,5 & 10/3\\
\hdashline
1,5,1 & 7/3\\
\hdashline
1,5,2 & 8/3\\
\hdashline
1,5,4 & 10/3\\
\hdashline
1,5,5 & 11/3\\
\hdashline
2,1,1 & 4/3\\
\hdashline
2,1,2 & 5/3\\
\hdashline
2,1,4 & 7/3\\
\hdashline
2,1,5 & 8/3\\
\hdashline
2,2,1 & 5/3\\
\hdashline
2,2,2 & 2\\
\hdashline
2,2,4& 8/3\\
\hdashline
2,2,5 & 3\\
\hdashline
2,4,1 & 7/3\\
\hdashline
2,4,2 & 8/3\\
\hdashline
2,4,4 & 10/3\\
\hdashline
2,4,5 & 11/3\\
\hdashline
2,5,1 & 8/3\\
\hdashline
2,5,2 & 3\\
\hdashline
2,5,4 & 11/3\\
\hdashline
2,5,5 & 4\\
\hdashline
4,1,1 & 2\\
\hdashline
4,1,2 & 7/3\\
\hdashline
4,1,4 & 3\\
\hdashline
4,1,5 & 10/3\\
\hdashline
4,2,1 & 7/3\\
\hdashline
4,2,2 & 8/3\\
\hdashline
4,2,4 & 10/3\\
\hdashline
4,2,5 & 11/3\\
\hdashline
4,4,1 & 3\\
\hdashline
4,4,2 & 10/3\\
\hdashline
4,4,4 & 4\\
\hdashline
4,4,5 & 13/3\\
\hdashline
4,5,1 & 10/3\\
\hdashline
4,5,2 & 11/3\\
\hdashline
4,5,4 & 13/3\\
\hdashline
4,5,5 & 14/3\\
\hdashline
5,1,1 & 7/3\\
\hdashline
5,1,2 & 8/3\\
\hdashline
5,1,4 & 10/3\\
\hdashline
5,1,5 & 11/3\\
\hdashline
5,2,1 & 8/3\\
\hdashline
5,2,2 & 3\\
\hdashline
5,2,4 & 11/3\\
\hdashline
5,2,5 &4\\
\hdashline
5,4,1 & 10/3\\
\hdashline
5,4,2 & 11/3\\
\hdashline
5,4,4 & 13/3\\
\hdashline
5,4,5 & 14/3\\
\hdashline
5,5,1 &11/3\\
\hdashline
5,5,2 & 4\\
\hdashline
5,5,4 & 14/3\\
\hdashline
5,5,5 & 5\\
\hdashline
\end{array} S am pl e v a l u es 1 , 1 , 1 1 , 1 , 2 1 , 1 , 4 1 , 1 , 5 1 , 2 , 1 1 , 2 , 2 1 , 2 , 4 1 , 2 , 5 1 , 4 , 1 1 , 4 , 2 1 , 4 , 4 1 , 4 , 5 1 , 5 , 1 1 , 5 , 2 1 , 5 , 4 1 , 5 , 5 2 , 1 , 1 2 , 1 , 2 2 , 1 , 4 2 , 1 , 5 2 , 2 , 1 2 , 2 , 2 2 , 2 , 4 2 , 2 , 5 2 , 4 , 1 2 , 4 , 2 2 , 4 , 4 2 , 4 , 5 2 , 5 , 1 2 , 5 , 2 2 , 5 , 4 2 , 5 , 5 4 , 1 , 1 4 , 1 , 2 4 , 1 , 4 4 , 1 , 5 4 , 2 , 1 4 , 2 , 2 4 , 2 , 4 4 , 2 , 5 4 , 4 , 1 4 , 4 , 2 4 , 4 , 4 4 , 4 , 5 4 , 5 , 1 4 , 5 , 2 4 , 5 , 4 4 , 5 , 5 5 , 1 , 1 5 , 1 , 2 5 , 1 , 4 5 , 1 , 5 5 , 2 , 1 5 , 2 , 2 5 , 2 , 4 5 , 2 , 5 5 , 4 , 1 5 , 4 , 2 5 , 4 , 4 5 , 4 , 5 5 , 5 , 1 5 , 5 , 2 5 , 5 , 4 5 , 5 , 5 S am pl e m e an ( X ˉ ) 1 4/3 2 7/3 4/3 5/3 7/3 8/3 2 7/3 3 10/3 7/3 8/3 10/3 11/3 4/3 5/3 7/3 8/3 5/3 2 8/3 3 7/3 8/3 10/3 11/3 8/3 3 11/3 4 2 7/3 3 10/3 7/3 8/3 10/3 11/3 3 10/3 4 13/3 10/3 11/3 13/3 14/3 7/3 8/3 10/3 11/3 8/3 3 11/3 4 10/3 11/3 13/3 14/3 11/3 4 14/3 5
The sampling distribution of the sample mean X ˉ \bar{X} X ˉ is
X ˉ f f ( X ˉ ) X f ( X ˉ ) X 2 f ( X ˉ ) 1 1 1 / 64 1 / 64 3 / 192 4 / 3 3 3 / 64 4 / 64 16 / 192 5 / 3 3 3 / 64 5 / 64 25 / 192 2 4 4 / 64 8 / 64 48 / 192 7 / 3 9 9 / 64 21 / 64 147 / 192 8 / 3 9 9 / 64 24 / 64 192 / 192 3 6 6 / 64 18 / 64 162 / 192 10 / 3 9 9 / 64 30 / 64 300 / 192 11 / 3 9 9 / 64 33 / 64 363 / 192 4 4 4 / 64 16 / 64 192 / 192 13 / 3 3 3 / 64 13 / 64 169 / 192 14 / 3 3 3 / 64 14 / 64 196 / 192 5 1 1 / 64 5 / 64 75 / 192 S u m = 64 1 3 59 / 6 \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
& 1 & 1 & 1/64 & 1/64 & 3/192\\
\hdashline
& 4/3 & 3 & 3/64 & 4/64 & 16/192 \\
\hdashline
& 5/3 & 3 & 3/64 & 5/64 & 25/192\\
\hdashline
& 2 & 4 & 4/64 & 8/64 & 48/192 \\
\hdashline
& 7/3 & 9 & 9/64 & 21/64 & 147/192 \\
\hdashline
& 8/3 & 9 & 9/64 & 24/64 & 192/192 \\
\hdashline
& 3 & 6 & 6/64 & 18/64 & 162/192 \\
\hdashline
& 10/3 & 9 & 9/64 & 30/64 & 300/192 \\
\hdashline
& 11/3 & 9 & 9/64 & 33/64 & 363/192 \\
\hdashline
& 4 & 4 & 4/64 & 16/64 & 192/192 \\
\hdashline
& 13/3 & 3 & 3/64 & 13/64 & 169/192 \\
\hdashline
& 14/3 & 3 & 3/64 & 14/64 & 196/192 \\
\hdashline
& 5 & 1 & 1/64 & 5/64 & 75/192 \\
\hdashline
Sum= & & 64 & 1 & 3 & 59/6
\\
\hdashline
\end{array} S u m = X ˉ 1 4/3 5/3 2 7/3 8/3 3 10/3 11/3 4 13/3 14/3 5 f 1 3 3 4 9 9 6 9 9 4 3 3 1 64 f ( X ˉ ) 1/64 3/64 3/64 4/64 9/64 9/64 6/64 9/64 9/64 4/64 3/64 3/64 1/64 1 X f ( X ˉ ) 1/64 4/64 5/64 8/64 21/64 24/64 18/64 30/64 33/64 16/64 13/64 14/64 5/64 3 X 2 f ( X ˉ ) 3/192 16/192 25/192 48/192 147/192 192/192 162/192 300/192 363/192 192/192 169/192 196/192 75/192 59/6
e. The mean of the sample means is
μ X ˉ = E ( X ˉ ) = 3 \mu_{ \bar{X}}=E(\bar{X})=3 μ X ˉ = E ( X ˉ ) = 3
V a r ( X ˉ ) = σ X ˉ 2 = E ( X ˉ 2 ) − ( E ( X ˉ ) ) 2 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
= 59 6 − ( 3 ) 2 = 5 6 =\dfrac{59}{6}-(3)^2=\dfrac{5}{6} = 6 59 − ( 3 ) 2 = 6 5 μ X ˉ = μ \mu_{\bar{X}}=\mu μ X ˉ = μ σ X ˉ 2 = σ 2 n \sigma_{\bar{X}}^2=\dfrac{\sigma^2}{n} σ X ˉ 2 = n σ 2
f. Standard deviation of the sampling distribution of sample means:
σ X ˉ = σ X ˉ 2 = 5 6 ≈ 0.91287 \sigma_{\bar{X}}=\sqrt{\sigma_{\bar{X}}^2}=\sqrt{\dfrac{5}{6}}\approx0.91287 σ X ˉ = σ X ˉ 2 = 6 5 ≈ 0.91287
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