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(Solved): WPC 300: Assignment 7 : Car Manufacturer : CarsData jmp (updated 26th March 2020)...


WPC 300 Assignment 7

Case Study: Car Manufacturer

(updated 26th March 2020)

A team charged with designing a new car in an automobile manufacturing company is concerned about the gasoline mileage that can be achieved. With the growing pressure from the government, the team is worried that the car’s mileage will result in violation of Corporate Average Fuel Economy (CAFE) regulations for vehicle efficiency, generating bad publicity and fines. Because of the anticipated weight of the car, the mileage attained in city driving is of particular concern.
The design team has a good idea of the characteristics of the car, right down to the type of leather to be used for the seats. However, the team does not know how these characteristics will affect the mileage.
You are hired to help the team. Your goal is two folds. First, you need to learn which characteristics of the design are likely to affect city mileage. The engineers want a model that they can rely on to predict the associated mileage for a car when designed.
You have access to the data file: CarsData.jmp. The data variables in the file are summarized in the following table.

WPC 300 Car Manufaturer

 

Case question:
Use the least square method to develop a linear regression model to predict the city mileage of a car using all other continuous attributes of a car in the data file.

  1. Show the screenshot of the effect summary table. [5 points]
  2. Remove the insignificant parameters from the model one by one by checking the log(worth) of each parameter. Keep doing this until you are left with parameters that are significant (p-value less than 5%). Show the screenshot of the “Effect Summary”, “Parameter Estimates” and “Analysis of Variance” tables from the JMP analysis. [5 points]
  3. Explain what you found out from the ANOVA table [2 points]. What is the R2 of your final model? [1 point] Explain the meaning of the obtained R2. [2 points]
  4. Based on the model, what are the most and least important variables in predicting the city mileage of a car? [5 points]
  5. Write down the equation of the regression model and give an interpretation of each significant coefficient of the model. [5points]


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