Question #204182

Consider a population of Senior High School consisting of the values 1, 2, 3,4, 5, and 6.

Compute the following:

1. population mean

2. population variance

3. population standard deviation

4. illustrate the probability histogram of the sampling distribution of the means​


1
Expert's answer
2021-06-08T04:43:29-0400

1.

We have population values 1,2,3,4,5,61,2,3,4,5,6 population size N=6.N=6. 


μ=1+2+3+4+5+66=3.5\mu=\dfrac{1+2+3+4+5+6}{6}=3.5

2.


σ2=1Ni(xiμ)2\sigma^2=\dfrac{1}{N}\sum_i(x_i-\mu)^2

σ2=16((13.5)2+(22.5)2+(33.5)2+(43.5)2\sigma^2=\dfrac{1}{6}\big((1-3.5)^2+(2-2.5)^2+(3-3.5)^2+(4-3.5)^2

(53.5)2+(63.5)2)=17.562.916667(5-3.5)^2+(6-3.5)^2\big)=\dfrac{17.5}{6}\approx2.916667

3.


σ=σ2=17.561.707825\sigma=\sqrt{\sigma^2}=\sqrt{\dfrac{17.5}{6}}\approx1.707825

4.

Let sample size n=2.n=2.Thus, the number of possible samples which can be drawn without replacement is


(Nn)=(62)=15\dbinom{N}{n}=\dbinom{6}{2}=15


2.


SampleSampleSample meanNo.values(Xˉ)11,23/221,34/231,45/241,56/251,67/262,35/272,46/282,57/292,68/2103,47/2113,58/2123,69/2134,59/2144,610/2155,611/2\def\arraystretch{1.5} \begin{array}{c:c:c} Sample & Sample & Sample \ mean \\ No. & values & (\bar{X}) \\ \hline 1 & 1,2 & 3/2 \\ \hdashline 2 & 1,3 & 4/2 \\ \hdashline 3 & 1,4 & 5/2 \\ \hdashline 4 & 1,5 & 6/2\\ \hdashline 5 & 1,6 & 7/2 \\ \hdashline 6 & 2,3 & 5/2 \\ \hline 7 & 2,4 & 6/2 \\ \hline 8 & 2,5 & 7/2 \\ \hline 9 & 2,6 & 8/2 \\ \hline 10 & 3,4 & 7/2 \\ \hline 11 & 3,5 & 8/2 \\ \hline 12 & 3,6 & 9/2 \\ \hline 13 & 4, 5 & 9/2 \\ \hline 14 & 4,6 & 10/2 \\ \hline 15 & 5,6 & 11/2 \\ \hline \end{array}





Xˉff(Xˉ)Xˉf(Xˉ)Xˉ2f(Xˉ)3/211/153/309/604/211/154/3016/605/222/1510/3050/906/222/1512/3072/607/233/1021/30147/608/222/1516/30128/609/222/1518/30162/6010/211/1510/30100/6011/211/1511/30121/60Total151105/30805/60\def\arraystretch{1.5} \begin{array}{c:c:c:c:c} \bar{X} & f & f(\bar{X}) & \bar{X}f(\bar{X})& \bar{X}^2f(\bar{X}) \\ \hline 3/2 & 1& 1/15 & 3/30 & 9/60 \\ \hdashline 4/2 & 1 & 1/15 & 4/30 & 16/60 \\ \hdashline 5/2 & 2 & 2/15 & 10/30 & 50/90 \\ \hdashline 6/2 & 2 & 2/15 & 12/30 & 72/60 \\ \hdashline 7/2 & 3 & 3/10 & 21/30 & 147/60 \\ \hdashline 8/2 & 2 & 2/15 & 16/30 & 128/60 \\ \hdashline 9/2 & 2& 2/15 & 18/30 & 162/60 \\ \hdashline 10/2 & 1 & 1/15 & 10/30 & 100/60 \\ \hdashline 11/2 & 1 & 1/15 & 11/30 & 121/60 \\ \hdashline Total & 15 & 1 & 105/30 & 805/60 \\ \hline \end{array}




E(Xˉ)=Xˉf(Xˉ)=10530=3.5E(\bar{X})=\sum\bar{X}f(\bar{X})=\dfrac{105}{30}=3.5

The mean of the sampling distribution of the sample means is equal to the

the mean of the population.



E(Xˉ)=3.5=μE(\bar{X})=3.5=\mu




Var(Xˉ)=Xˉ2f(Xˉ)(Xˉf(Xˉ))2Var(\bar{X})=\sum\bar{X}^2f(\bar{X})-(\sum\bar{X}f(\bar{X}))^2




=80560(10530)2=761.666667=\dfrac{805}{60}-(\dfrac{105}{30})^2=\dfrac{7}{6}\approx1.666667




Var(Xˉ)=761.080123\sqrt{Var(\bar{X})}=\sqrt{\dfrac{7}{6}}\approx1.080123

Verification:


Var(Xˉ)=σ2n(NnN1)=17.56(2)(6261)Var(\bar{X})=\dfrac{\sigma^2}{n}(\dfrac{N-n}{N-1})=\dfrac{17.5}{6(2)}(\dfrac{6-2}{6-1})=3.531.666667,True=\dfrac{3.5}{3}\approx1.666667, True




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