(Solved): The variance of the OLS estimator for the univariate model slope coefficient decreases as: ( selec ...

The variance of the OLS estimator for the univariate model slope coefficient decreases as: ( select all correct answers ) variance of the error term (u) decreases the variance of \( \mathrm{x} \) increases sample size \( (n) \) increases The following equality relies on which key assumption? \[ \sum_{i-1}^{n}\left(x_{i}-\bar{x}\right)^{2} \operatorname{var}\left(u_{i} \mid x\right)=\sigma^{2} \sum_{i=1}^{n b}\left(x_{i}-\bar{x}\right)^{2} \] SLR1: population regression function is linear in parameters SLR2: data are a random sample from the population SLR4: zero conditional mean SLR5: homoskedasticity