Suppose samples of size 2 are drawn from the population. List all the possible samples and the corresponding means.
All possible samples:{(2,5), (2,8), (5,8)}.
Sample means for these samples: 3.5, 5, 6.5.
Mean of the sample means: "\\dfrac{(3.5+5+6.5)}{3}=5."
Population mean:"\\dfrac{(2+5+8)}{3}=5."
So, the sample mean is an unbiased estimate of the population mean.
Population variance: "\\sigma^2=\\frac{(2-5)^2+(5-5)^2+(8-5)^2}{3}=6."
The variance of the sampling distribution of means: "\\sigma_x^2=\\frac{\\sigma^2(N-n)}{n(N-1)}=\\frac{6(3-2)}{2(3-1)}=\\frac{3}{2}"
The standard deviation of the sampling distribution of means: "\\sigma_x=\\sqrt{\\frac{3}{2}}"
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