The CEO of a well-known car reseller company wants to determine the factors driv
ID: 2947543 • Letter: T
Question
The CEO of a well-known car reseller company wants to determine the factors driving the resale value of a vehicle. The CEO knows that the resale value is an important factor considered by customers when buying a car. Assume you are performing a regression analysis using the data provided in the table below showing resale value, suggested price and type of vehicle (sport utility, small pickup).
Suggested Resale Value Type of Vehicle Sport Utility Sport Utility Sport Utility Sport Utility Sport Utility Sport Utility Sport Utility Sport Utility Sport Utility Sport Utility Price (S 9,495 20,495 26,789 18,965 30,186 25,745 29,895 26,919 22,418 17,148 18,847 16,870 18,510 20,225 16,938 16,820 23,050 12,110 18,228 19.318 15,000 Vehicle Chevrolet Blazer LS Ford Explorer Sport GMC Yukon XL 1500 Honda CR-V 57 67 57 Jeep Cherokee Limited Mercury Mountaineer Nissan Pathfinder XE Toyota 4Runner Toyota RAV4 Cuexvolet S-10 Extended Cab Small Pickup Dodge Dakota Club Cab Sport Sma Pickup Ford Ranger XLT Regular Cab Sma Pickup 48 30000 Ford Ranger XLT Sueeab Small Pickup Small Pickup Small Pickup a. 2pt) How would you include "Type ofMazda B4000 SE Cab Plus Small Pickup 10000 5000 Suggested Retail Price (5) GMC Sonoma Regular Cab lsuzu Hombre pacecab 41 vehicle" in the regression analysis? Nissan FrontierXE Regular Toyota Tacoma Stracab Toyota Tacoma XtracabV6 Small Pickup Small Pickup Small Pickup Small Picku 49 50 60 b. (2pt) Comment on the scatter plot for resale value and suggested priceExplanation / Answer
a) Here the value of R2 is 0.193 which is close to zero. So, we can conclude that the 19.3$% variability of Resalevalue can be explained by Suggestedprice. So, the model is not good.
b) Here we can notice that the errors are concentrated near zero. So, normality assumption holds.
c) Here the observed value of F statistic is 6.952. Now, p-value will be P[F1,15 > 6.952] = 0.01868238. So, we can't say the model has any effect at 1% level of significance but at 5% level of significance we can say the model has an effect.
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