Refer to the CDI data set . The number of active physicians in a CDI (y) (Column 8) is expected to be related to total population (Column 5), number of hospital beds (Column 9), and total personal income (Column 16). Assume that first-order regression model (Lecture 2 Eqn. (1)) is appropriate for each of the three predictor variables.

a. Regress the number of active physicians in turn on each of the three predictor variables. State the estimated regression functions.

b. Plot the three estimated regression functions and data on separate graphs. Does a linear regression relation appear to provide a good fit for each of the three predictor variables?

c. Calculate MSE for each of the three predictor variables. Which predictor variable leads to the smallest variability around the fitted regression line?

Could someone helps me out? Could someone kindly show how to use python (coding) to solve these questions? I am very grateful.