Question

In this assignment, you will be using a regression tree to analyze some data about contract negotiations.

Athlete Contract Negotiations (regression tree). 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-field performance (Awards), the number of games the athlete has missed due to injury (GamesMissed), and millions of dollars of guaranteed money in the athlete's most recent contract (Money, dependent variable).

Answer 1

From the available information, the given data is displayed below: SnapPercent 90.28 106 96 SnapPercent SnapPercent 85.09 95.37 53 53 71 25 Awards Awards 14.73 20.71 6.75 7.25 11 14 48 23 Games Missed Games Missed Additional amount 1.5 32.52 2.5 46.73 048 0 11 50 23.61 47.83 32.74

(a) Observe the tree diagram, Titu's Johnston's variable values are: Snap percent=96 Awards=7 And Games missed=3. Snap percent = 96 → Awards = 7 → Games missed = 3 + 32.74 The predicted money that Titus Johnson's profile should earn in his contract is, $32.74 million of guaranteed money. (b) Casey feels that if Titus had won additional award, The additional guaranteed money would result in prediction amount is 46.73 million of guaranteed money. The increase in money with and additional award is calculated as, Increase in money = Additional guaranteed money - Guaranteed money from part(a), the =46.73-32.74 guamteed money is 32.74 13.99 Therefore, An additional award would result in a predicted amount of $46.73 million of guaranteed money which corresponds to an increase of $13.99 million over part(a).