Use Python in Google Colab to download your dataset "insurance.csv", to explore and summarize the data as follows: Replace missing values with the mean values. Run any method to convert three categorical variables (sex, smoker, and region) to numerical variables using any of: LabelEncoder(), OneHotEncoder(), Dummy Variables. Split the data into 70% train, 30% test, then use LinearRegression package to predict charges as function of: charges =f ('age', 'sex', 'bmi','children', 'smoker', 'region') o Find the values of: "R^2 with scale" o Find the values of: "Model Coefficient" o Find the values of: "Model Intercept