Regression with categorical predictors    The insurance.csv data base contains insurance information for 1338 people. The columns report the age, sex, BMI, number of children, smoker status, and geographical region of each individual, as well as the insurance charges.        Load the data set into a data frame.    Recode the categorical variable smoker into a dummy variable, smoke.    Use the ols function to perform a multiple regression with charges as the response variable and age, bmi, and smoke, in that order, as the predictor variables    Create an analysis of variance table using the results of the multiple regression.    If the number of children is used instead of BMI, the output is:                          sum_sq      df            F        PR(>F)    age         1.963476e+10     1.0   483.557436  1.062319e-91    children    4.592837e+08     1.0    11.311064  7.923099e-04    smoker_yes  1.237765e+11     1.0  3048.320439  0.000000e+00    Residual    5.416683e+10  1334.0          NaN           NaN