Consider a population consisting of 1,2,3,4 and 5. Supposed samples of size 2 are drawn from this population. describe the sampling distribution of the sample means.
Here population size : N = 5
and which are 1,2,3,4 and 5
And we have to draw a sample of size 2
So, there are "^{N}C_n" possible samples
that is, "^{5}C_2= 10"
Mean of population "(\\mu)" = "\\dfrac{1+2+3+4+5}{5}=3"
Variance of population "(\\sigma^2)=\\dfrac{\\Sigma(x_i-\\bar{x})^2}{n}=\\dfrac{4+1+0+1+4}{5}=2"
So all the possible samples are:
(1,2),(1,3),(1,4),(1,5),(2,3),(2,4),(2,5),(3,4),(3,5) and (4,5)
Mean of sampling distribution "(\\mu_{\\bar{x}})=\\mu=3"
The variance of sampling distribution "(\\sigma^2_{\\bar{x}})= \\dfrac{\\sigma^2}{N}=\\dfrac{4}{5}=0.8"
So mean of population = mean of sample = 3
Variance of population = 2 and variance of sample = 0.8
Histogram of the mean of population:
Histogram of the mean of sampling:
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