i$)$ Generate a response $Y$ and two predictors $x1$ and $x2,$ with $n=100$

ii$)$ Initialize ${}_1$ to take on a value of your choice. It does not matter what

value you choose.

iii$)$ Keeping ${}_1$ fixed, fit the model $Y-{}_1{x}_1={}_2+x_2+$

iv$)$ Keeping $,$ fixed, fit the model $Y-{}_2{x}_2={}_0+{}_1{x}_1+$

v$)$ Write a for loop to repeat $($iii$)$ and $($iv$)1000$ times. Report the estimates

of ${}_0,{}_1$ and ${}_2$ at each iteration of the for loop. Create a plot in which

each of these values is displayed, with ${}_0,{}_1,$ and ${}_2$ each shown in a

different color.

vi$)$ Compare your answer in $($v$)$ to the results of simply performing multiple

linear regression to predict $Y$ using $x1$ and $x2.$ Use the abline$()$ function

to overlay those multiple linear regression coefficient estimates on the

plot obtained in $($v$).$