Read the Case Study "Reagan Racing".
Assignments
Part 1
John Reagan decides to ignore any potential role temperature might play, and asks you - his consultant - to compute the Expected Monetary value of each option, i.e., for racing and for not racing
Your assignment is to compute the Expected Monetary value of each option, i.e., for racing and for not racing: Show your work, and explain your basis for each step in the process
What do you recommend, based on the Expected Monetary value of each option? Why is that?
Part 2
Based on the historical data from the 24 races, compute a regression that predicts number of cracks on the basis of temperature.
Based on the historical data from the 24 races, compute a regression that predicts number of cracks on the basis of log of temperature.
Is/Are these regression(s) statistically significant? Show your work, and explain your basis for each step in the process
Use the better regression to forecast the number of cracks at a race temp of 38 degrees.
How do these findings affect your advice about racing versus not racing? Why is that?
Part 3
Say that you had time (3 months) to make some extra preparations for the Pocono race, while still using the unique engine design. The race will be on a day with a temp of 38 degrees. Considering your regression results for number of cracks that would be expected, what ideas might you suggest be implemented, to reduce your chances of blowing the engine, while still ending "in the money?" Why is that?
Show your work, and explain your basis for each step in the process.