In the following regression model Yi = α + βXi + ei, under the usual assumptions, variance of b̂ is given by :
1
σ2
2
\( \frac{\sigma^2}{\Sigma\left(\mathrm{X}_i-\overline{\mathrm{X}}\right)^2} \)
3
\( \frac{\Sigma\left(\mathrm{X}_i-\overline{\mathrm{X}}\right)^2}{\sigma^2}\)
4
\( \frac{\Sigma\left(\mathrm{Y}_i-\overline{\mathrm{Y}}\right)^2}{\sigma^2}\)