please answer a, b, c

Casey Deesel is a sports agent negotiating a contract for Titus Johnston, an athlete in the National Football League (NFL). An important aspect of any NFL contract is the amount of guaranteed money over the life of the contract. Casey has gathered data on 506 NFL athletes who have recently signed new contracts: Each observation (NFL athlete) includes values for percentage of his team's plays that the athlete is on the field (SnapPercent), the number of awards an athlete has received recognizing on-fleld performance (Awards), the number of games the athlete has missed due to injury (GamesMissed), and millions of dollars of quaranteed money in the athlete's most recent contract (Money, dependent variable). Casey has trained a full regression tree on 304 observations and then used the validation set to prune the tree to obtain a best-pruned tree. The best-pruned tree (as applied to the 202 observations in the validation set) is: SnapPercent (a) Thtui Johnstah's variable values are: Snappercent - 94. Awards - 6 , and Gamea Mased = 2. How much guaronteed money does the regression tree predict that a player with Titu1. Jotision's profle should earn in his contract? If required, round your answers to two decimal places. The predleted resuit is million of guaranted money (b) Cisey feels thot Thas was denied an addibonal award in the past seavon due to some questionable voting by some sports media, If Titus hod won this additional award, how mych additional guaranteed money would the regresiven tree predict for mious versos the prediction in part (0) ? 1. An addilonal zward would not change the amount of guaranteed money. 11. An additional award would increase the amount of guaranteed money by \$\$\$.91 milach. III. An additional ansid would increase the ancunt of guaranteed money by $13.99 milion. IV. An additional award would increase the amount of guaranteed money by $17.79 million. V. An additional award would increase the amount of guaranteed money by $26.02 millon. (c) As Casey reviewi the best-pruned tree, he is confused by the leaf node corresponding to the sequence of decision rules of "Snappercent 290.28,5nsppercent295.37, Awards 7.25, CamesMissed e 2.5. " This requence of decision rules results in an estimate of $47.83 mallion of guaranteed money, tut the tree states that zero observations occur in the corresponding partion. If zero observations octur in this portition, how can the regression tree provide an estimate of 559 millon? Explain this part of the regression tree to Casey by referting how the bert-pruned tree a behined. The prediched quaranteed money of 347.83 million for observatioas sstishinn -Gnanpercent 290.28,5 Snappercent 295,37 , Awards 95.37, Awards