USE R programming

Problem 1. Linear Regression: Please answer the following questions using the West Roxbury Neighborhood data (west_roxbury_Modified_A5.csv). This data set contains 15 variables as listed below: 1. [1 point] Please import the data into R,and name the dataframe "home data". Convert the columns FULL.BATH and REMODEL in the "home data" to categorical variables using as.factor(). Please make sure to update the column types in the "home data". 2. [0.5 point] Create a new column in the home data, named "AGE", to represent the age of the property, computed as the current year, minus the Year the property was built. 3. [1 point] Create a new column in the homedata, named High.Tax For each row, High.Tax is 1 if the "TAX" is greater than the "TAX" column's median, and 0 otherwise. 4. [1 point] Randomly partition the data into a training set (60\%) and a validation set (40\%). Use 100 as the argument of the setseed() function. 5. [1 point] Build a linear regression model to predict the TAX using LIVING.AREA, AGE, and FULL.BATH as predictor variables. 6. [2 points] Interpret the coefficient estimates for each predictor variable (i.e. how does change in the value of each predictor variable impact the value of the target variable)? Which predictors are significant? 7. [4 points] Obtain the accuracy performance measures for your model applied to both training and validation data. 8. [1 point] Is your model over-fitted? Discuss your