Question #247692
Suppose a small finite population consists of only N = 5 numbers:

54 55 59 63 64

I. Find population mean and standard deviation
II. Draw all possible samples of size 2 with replacement
III. Construct sampling distribution
IV. Find sample mean and standard deviation
V. Verify/justify your results.
1
Expert's answer
2021-10-13T11:54:29-0400

I.


mean=μ=54+55+59+63+645=59mean=\mu=\dfrac{54 +55 +59+ 63 +64}{5}=59

variance=σ2=15((5459)2+(5559)2variance=\sigma^2=\dfrac{1}{5}((54-59)^2+(55-59)^2

+(5959)2+(6359)2+(6459)2)=16.4+(59-59)^2+(63-59)^2+(64-59)^2)=16.4

σ=σ2=16.4=24.1\sigma=\sqrt{\sigma^2}=\sqrt{16.4}=2\sqrt{4.1}

II. There are 52=255^2=25 samples of size two which can be drawn with replacement: 


SampleSample mean(54,54)54(54,55)54.5(54,59)56.5(54,63)58.5(54,64)59(55,54)54.5(55,55)55(55,59)57(55,63)59(55,64)59.5(59,54)56.5(59,55)57(59,59)59(59,63)61(59,64)61.5(63,54)58.5(63,55)59(63,59)61(63,63)63(63,64)63.5(64,54)59(64,55)59.5(64,59)61.5(64,63)63.5(64,64)64\begin{matrix} Sample & Sample\ mean \\ (54,54) & 54 \\ (54,55) & 54.5 \\ (54,59) & 56.5 \\ (54,63) & 58.5 \\ (54,64) & 59 \\ (55,54) & 54.5 \\ (55,55) & 55\\ (55,59) & 57 \\ (55,63) & 59 \\ (55,64) & 59.5 \\ (59,54) & 56.5 \\ (59,55) & 57 \\ (59,59) & 59 \\ (59,63) & 61 \\ (59,64) & 61.5 \\ (63,54) & 58.5 \\ (63,55) & 59\\ (63,59) & 61 \\ (63,63) & 63 \\ (63,64) & 63.5 \\ (64,54) & 59 \\ (64,55) & 59.5 \\ (64,59) & 61.5 \\ (64,63) & 63.5 \\ (64,64) & 64 \\ \end{matrix}

III.



XˉP(Xˉ)541/2554.52/25551/2556.52/25572/2558.52/25595/2559.52/25612/2561.52/25631/2563.52/25641/25\begin{matrix} \bar{X} & P(\bar{X}) \\ 54 & 1/25 \\ 54.5 & 2/25 \\ 55 & 1/25 \\ 56.5 & 2/25 \\ 57 & 2/25 \\ 58.5 & 2/25 \\ 59 & 5/25\\ 59.5 & 2/25 \\ 61 & 2/25 \\ 61.5 & 2/25 \\ 63 & 1/25 \\ 63.5 & 2/25 \\ 64 & 1/25 \\ \end{matrix}

IV.


μXˉ=54(125)+54.5(225)+55(125)+56.5(225)\mu_{\bar{X}}=54(\dfrac{1}{25})+54.5(\dfrac{2}{25})+55(\dfrac{1}{25})+56.5(\dfrac{2}{25})

+57(225)+58.5(225)+59(525)+59.5(225)+57(\dfrac{2}{25})+58.5(\dfrac{2}{25})+59(\dfrac{5}{25})+59.5(\dfrac{2}{25})

+61(225)+61.5(225)+63(125)+63.5(225)+61(\dfrac{2}{25})+61.5(\dfrac{2}{25})+63(\dfrac{1}{25})+63.5(\dfrac{2}{25})

+64(125)=59+64(\dfrac{1}{25})=59


iXˉi2P(Xiˉ)=542(125)+54.52(225)+552(125)\sum_i\bar{X}_i^2P(\bar{X_i})=54^2(\dfrac{1}{25})+54.5^2(\dfrac{2}{25})+55^2(\dfrac{1}{25})

+56.52(225)+572(225)+58.52(225)+592(525)+56.5^2(\dfrac{2}{25})+57^2(\dfrac{2}{25})+58.5^2(\dfrac{2}{25})+59^2(\dfrac{5}{25})

+59.52(225)+612(225)+61.52(225)+632(125)+59.5^2(\dfrac{2}{25})+61^2(\dfrac{2}{25})+61.5^2(\dfrac{2}{25})+63^2(\dfrac{1}{25})

+63.52(225)+642(225)=3489.2+63.5^2(\dfrac{2}{25})+64^2(\dfrac{2}{25})=3489.2

σXˉ2=iXˉi2P(Xiˉ)μXˉ2=3489.2592=8.2\sigma_{\bar{X}}^2=\sum_i\bar{X}_i^2P(\bar{X_i})-\mu_{\bar{X}}^2=3489.2-59^2=8.2

σXˉ=σXˉ2=8.2\sigma_{\bar{X}}=\sqrt{\sigma_{\bar{X}}^2}=\sqrt{8.2}

μXˉ=59,σXˉ=8.2\mu_{\bar{X}}=59, \sigma_{\bar{X}}=\sqrt{8.2}

V.

The mean μXˉ\mu_{\bar{X}} and standard deviation σXˉ\sigma_{\bar{X}} of the sample mean Xˉ\bar{X} satisfy


μXˉ=59=μ,σXˉ=8.2=24.12=σn\mu_{\bar{X}}=59=\mu, \sigma_{\bar{X}}=\sqrt{8.2}=\dfrac{2\sqrt{4.1}}{\sqrt{2}}=\dfrac{\sigma}{\sqrt{n}}


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