1.
a. We have population values 6,9,12,15,18,21, population size N=6 and sample size n=3.
Mean of population ( μ ) (\mu) ( μ ) = 6 + 9 + 12 + 15 + 18 + 21 6 = 13.5 \dfrac{6+9+12+15+18+21}{6}=13.5 6 6 + 9 + 12 + 15 + 18 + 21 = 13.5
Variance of population
σ 2 = Σ ( x i − x ˉ ) 2 n = 1 6 ( 56.25 + 20.25 + 2.25 \sigma^2=\dfrac{\Sigma(x_i-\bar{x})^2}{n}=\dfrac{1}{6}(56.25+20.25+2.25 σ 2 = n Σ ( x i − x ˉ ) 2 = 6 1 ( 56.25 + 20.25 + 2.25
+ 2.25 + 20.25 + 56.25 ) = 26.25 +2.25+20.25+56.25)=26.25 + 2.25 + 20.25 + 56.25 ) = 26.25
σ = σ 2 = 26.25 ≈ 5.1235 \sigma=\sqrt{\sigma^2}=\sqrt{26.25}\approx5.1235 σ = σ 2 = 26.25 ≈ 5.1235 Select a random sample of size 3 without replacement. We have a sample distribution of sample mean.
b. The number of possible samples which can be drawn without replacement is N C n = 6 C 3 = 20. ^{N}C_n=^{6}C_3=20. N C n = 6 C 3 = 20.
c.
n o S a m p l e S a m p l e m e a n ( x ˉ ) 1 6 , 9 , 12 9 2 6 , 9 , 15 10 3 6 , 9 , 18 11 4 6 , 9 , 21 12 5 6 , 12 , 15 11 6 6 , 12 , 18 12 7 6 , 12 , 21 13 8 6 , 15 , 18 13 9 6 , 15 , 21 14 10 6 , 18 , 21 15 11 9 , 12 , 15 12 12 9 , 12 , 18 13 13 9 , 12 , 21 14 14 9 , 15 , 18 14 15 9 , 15 , 21 15 16 9 , 18 , 21 16 17 12 , 15 , 18 15 18 12 , 15 , 21 16 19 12 , 18 , 21 17 20 15 , 18 , 21 18 \def\arraystretch{1.5}
\begin{array}{c:c:c:c:c}
no & Sample & Sample \\
& & mean\ (\bar{x})
\\ \hline
1 & 6,9,12 & 9 \\
\hdashline
2 & 6,9,15 & 10 \\
\hdashline
3 & 6,9,18 & 11 \\
\hdashline
4 & 6,9,21 & 12 \\
\hdashline
5 & 6,12,15 & 11 \\
\hdashline
6 & 6,12,18 & 12 \\
\hdashline
7 & 6,12, 21 & 13 \\
\hdashline
8 & 6,15,18 & 13 \\
\hdashline
9 & 6,15,21 & 14 \\
\hdashline
10 & 6, 18,21 & 15 \\
\hdashline
11 & 9,12,15 & 12 \\
\hdashline
12 & 9, 12,18 & 13 \\
\hdashline
13 & 9, 12, 21 & 14 \\
\hdashline
14 & 9,15,18 & 14 \\
\hdashline
15 & 9,15,21 & 15 \\
\hdashline
16 & 9, 18,21 & 16 \\
\hdashline
17 & 12, 15,18 & 15 \\
\hdashline
18 & 12, 15,21 & 16 \\
\hdashline
19 & 12, 18,21 & 17 \\
\hdashline
20 & 15, 18,21 & 18 \\
\hdashline
\end{array} n o 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 S am pl e 6 , 9 , 12 6 , 9 , 15 6 , 9 , 18 6 , 9 , 21 6 , 12 , 15 6 , 12 , 18 6 , 12 , 21 6 , 15 , 18 6 , 15 , 21 6 , 18 , 21 9 , 12 , 15 9 , 12 , 18 9 , 12 , 21 9 , 15 , 18 9 , 15 , 21 9 , 18 , 21 12 , 15 , 18 12 , 15 , 21 12 , 18 , 21 15 , 18 , 21 S am pl e m e an ( x ˉ ) 9 10 11 12 11 12 13 13 14 15 12 13 14 14 15 16 15 16 17 18
d.
X ˉ f ( X ˉ ) X ˉ f ( X ˉ ) X ˉ 2 f ( X ˉ ) 9 1 / 20 9 / 20 81 / 20 10 1 / 20 10 / 20 100 / 20 11 2 / 20 22 / 20 242 / 20 12 3 / 20 36 / 20 432 / 20 13 3 / 20 39 / 20 507 / 20 14 3 / 20 42 / 20 588 / 20 15 3 / 20 45 / 20 675 / 20 16 2 / 20 32 / 20 512 / 20 17 1 / 20 17 / 20 289 / 20 18 1 / 20 18 / 20 324 / 20 \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
9 & 1/20 & 9/20 & 81/20 \\
\hdashline
10 & 1/20 & 10/20 & 100/20 \\
\hdashline
11 & 2/20 & 22/20 & 242/20 \\
\hdashline
12 & 3/20 & 36/20 & 432/20 \\
\hdashline
13 & 3/20 & 39/20 & 507/20 \\
\hdashline
14 & 3/20 & 42/20 & 588/20 \\
\hdashline
15 & 3/20 & 45/20 & 675/20 \\
\hdashline
16 & 2/20 & 32/20 & 512/20 \\
\hdashline
17 & 1/20 & 17/20 & 289/20 \\
\hdashline
18 & 1/20 & 18/20 & 324/20 \\
\hdashline
\end{array} X ˉ 9 10 11 12 13 14 15 16 17 18 f ( X ˉ ) 1/20 1/20 2/20 3/20 3/20 3/20 3/20 2/20 1/20 1/20 X ˉ f ( X ˉ ) 9/20 10/20 22/20 36/20 39/20 42/20 45/20 32/20 17/20 18/20 X ˉ 2 f ( X ˉ ) 81/20 100/20 242/20 432/20 507/20 588/20 675/20 512/20 289/20 324/20
e. Mean of sampling distribution
μ X ˉ = E ( X ˉ ) = ∑ X ˉ i f ( X ˉ i ) = 270 20 = 13.5 = μ \mu_{\bar{X}}=E(\bar{X})=\sum\bar{X}_if(\bar{X}_i)=\dfrac{270}{20}=13.5=\mu μ X ˉ = E ( X ˉ ) = ∑ X ˉ i f ( X ˉ i ) = 20 270 = 13.5 = 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 = 3750 20 − ( 13.5 ) 2 = 5.25 = σ 2 n ( N − n N − 1 ) =\dfrac{3750}{20}-(13.5)^2=5.25= \dfrac{\sigma^2}{n}(\dfrac{N-n}{N-1}) = 20 3750 − ( 13.5 ) 2 = 5.25 = n σ 2 ( N − 1 N − n )
σ X ˉ = 5.25 ≈ 2.2913 \sigma_{\bar{X}}=\sqrt{5.25}\approx2.2913 σ X ˉ = 5.25 ≈ 2.2913
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