Question #341253

Consider a population consisting of 2.3.4 and 6 illustrate the situation by doing the following:





1.Compute the mean and variance of the population





2.list all possible samples of size 2





3.construct the sampling distribution of the sample





4. Compute the mean and standard deviation of the sampling distribution of the sample means





5.construct the histogram.



Expert's answer

We have population values 2,3,4,6, population size N=4 and sample size n=2.

1. Mean of population (μ)(\mu) = 2+3+4+64=3.75\dfrac{2+3+4+6}{4}=3.75

Variance of population 


σ2=Σ(xixˉ)2n=14(3.0625+0.5625\sigma^2=\dfrac{\Sigma(x_i-\bar{x})^2}{n}=\dfrac{1}{4}(3.0625+0.5625


+0.0625+5.0625)=2.1875=3516+0.0625+5.0625)=2.1875=\dfrac{35}{16}

σ=σ2=2.18751.47902\sigma=\sqrt{\sigma^2}=\sqrt{2.1875}\approx1.47902

2. Select a random sample of size 2 without replacement. We have a sample distribution of sample mean.

The number of possible samples which can be drawn without replacement is NCn=4C2=6.^{N}C_n=^{4}C_2=6.

noSampleSamplemean (xˉ)12,35/222,46/232,68/243,47/253,69/264,610/2\def\arraystretch{1.5} \begin{array}{c:c:c:c:c} no & Sample & Sample \\ & & mean\ (\bar{x}) \\ \hline 1 & 2,3 & 5/2 \\ \hdashline 2 & 2,4 & 6/2 \\ \hdashline 3 & 2,6 & 8/2 \\ \hdashline 4 & 3,4 & 7/2 \\ \hdashline 5 & 3,6 & 9/2 \\ \hdashline 6 & 4,6 & 10/2 \\ \hdashline \end{array}



3.


Xˉf(Xˉ)Xˉf(Xˉ)Xˉ2f(Xˉ)5/21/65/1225/246/21/66/1236/247/21/67/1249/248/21/68/1264/249/21/69/1281/2410/21/610/12100/24\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 5/2 & 1/6 & 5/12 & 25/24 \\ \hdashline 6/2 & 1/6 & 6/12 & 36/24 \\ \hdashline 7/2 & 1/6 & 7/12 & 49/24 \\ \hdashline 8/2 & 1/6 & 8/12 & 64/24 \\ \hdashline 9/2 & 1/6 & 9/12 & 81/24 \\ \hdashline 10/2 & 1/6 & 10/12 & 100/24 \\ \hdashline \end{array}



4. Mean of sampling distribution 

μXˉ=E(Xˉ)=Xˉif(Xˉi)=4512=154=3.75=μ\mu_{\bar{X}}=E(\bar{X})=\sum\bar{X}_if(\bar{X}_i)=\dfrac{45}{12}=\dfrac{15}{4}=3.75=\mu



The variance of sampling distribution 

Var(Xˉ)=σXˉ2=Xˉi2f(Xˉi)[Xˉif(Xˉi)]2Var(\bar{X})=\sigma^2_{\bar{X}}=\sum\bar{X}_i^2f(\bar{X}_i)-\big[\sum\bar{X}_if(\bar{X}_i)\big]^2=35524(154)2=3548=σ2n(NnN1)=\dfrac{355}{24}-(\dfrac{15}{4})^2=\dfrac{35}{48}= \dfrac{\sigma^2}{n}(\dfrac{N-n}{N-1})

σXˉ=35480.85391\sigma_{\bar{X}}=\sqrt{\dfrac{35}{48}}\approx0.85391

5.


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