$i,$ from the $population{a}_{i}is$ the intercept for unit i and $b_{i}is$ the slope:

$y_i=a_i+b_i{x}_i$

With a random sample $of$ size $n,$ you implicitly draw $n$ values $of{b}_i$ along with $n$ values $of{a}_{i}x$ and $y{a}_i=+c_i$ and $b_i=+d_i,$ then $d_{i}is$

$.$

Substituting $a_i=+c_i$ and $b_i=+d_i$ into the initial model yields the following:

$y_i=+x_i+u_i,$ where $u_i=c_i+d_i{x}_i$

True $or$ False: $If{a}_{i}is$ uncorrelated with $x_i$ and $b_{i}is$ uncorrelated with $x_i$ and $x_i^2,$ then OLS consistently estimates $$ and $.$

True

False