I worked on the survey dataset, which was then split into a training and test set, calculated the average service time for each survey type, and came up with characteristics and target variables for a linear regression model. The test set service times are then predicted and the script uses matplotlib to display the regression line and RMSE (root mean square error) to estimate the model. The final result is a figure that shows how average usage time is predicted using a linear regression model depending on the type of study.