Please help

1. Model Fitting. (a) Enter the data into two vectors. Recall that in the demonstration video, this was accomplished by the following commands: > X y summary (troyslm) 2. Some predictions and fitted values. (a) Give the predicted drill time when starting at depths of 100ft, 146ft and 181ft. In the demonstration video, this was accomplished for 2 values as follows: > troysNewx predict (troysim, newdata=data. frame (x=troysNewx)) 2 2. 328571 4.546429 (b) Produce the fitted values for your model. In the demonstration video, this was accomplished with the following commands: > fitted(troyslm) 3. Residuals. (a) Produce the residuals for your model. In the demonstration video, this was accomplished as follows: > residtfroyslm) (b) Produce the squared residuals. In the demonstration video, this was accomplished as follows: > residtfroyslm) -2 (c) Produce the sum of squared residuals. In the demonstration video, this was accomplished as follows: > sum (resid troyslm) -2) [1] 4. 964286Directions: The expectations for the presentation of answers in this homework are extremely low. For example, in one question you will be asked to give the simple linear regression least squares fitted line. It will be acceptable to just copy and paste the R commands and summary() output to a simple text editor and submit electronically. You can work together on this homework but please make sure you understand the methods and submit your own work. For dry drilling, compressed air is forced down the drill rods to flush the cutting and drive the hammer. An experiment was conducted to determine if dry drill time increases with starting depth. x represents the starting depth in feet and y is the time required to drill 5 feet. obs Depth (x) Drill Time (y) 0 1.90 50 6.19 75 5.57 100 5.17 125 6.89 150 7.05 175 7.11 200 6.19 225 8.28 275 8.29 300 3.91 12 325 8.54 13 350 11.79 14 375 12.12 15 395 11.02 12 10 Time (Minutes) 8 6 4 2 0 100 200 300 400 Depth (Feet)