The goal of this case study is to carry out multiple linear regression based on the food service transport company dataset as attached within the first module as a CSV file named "Food service dataset.csv". a. Using sales as a dependent variable and quantity and weight as independent variables perform multiple linear regression using either excel, R, or Python. b. Interpret the output of the regression model in terms of statistical significance of variables (if any), p-values, R-squared, t-test, F-test, and coefficients for independent variables. c. Now split or divide the data set into two parts: 80% for training the model or as a training dataset and 20% for testing the model or test dataset. Repeat the linear regression model from part i on the two datasets. Does the model overfit? d. (Optional) Find the accuracy of the model using the ROC curve using either excel, R, or Python