Write the Rcode to do the following: load the SeatBelts(PetrolPrice,DriversKilled) dataset package via data(SeatBelts). Convert the object to dataframe. Assume new petrol price denoted as PP to be computed using mean(PetrolPrice)/Sd(PetrolPrice) and new kms, to be denoted as new_kms = mean (km)1000. Fit the linear model with new values where DriversKilled is the outcome and predictors are PP and new_kms. Also predict the number of driver deaths at the mean kms and average PetrolPrice levels. Write the Rcode to get the best fit line based on least square criteria using GaltonFamilies data with child's height as predictor and parents height as outcome. Compute the slope after re-centering the data. Also mention the code to verify the output using linear model formula. Write the Rcode to show that the normalizing the variable results in the slope being correlation. Use Galton data with parents height as predictor and child heights as outcome