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WPC 300 Hands-on Assignment-5

Car Manufacturer

One word documents with all necessary screen shots from JMP analysis and your answers to all questions.
You must write your name and student ID on the first page of the document. All answers should be in double space, 11-point font.
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.

Case question:
Use the least square method to develop a linear model to predict the city mileage of a car given all other continuous attributes of a car in the data file. Show screenshot of “Effect Summary” from JMP. [5 points]
a. Remove the insignificant parameters from the model one by one by checking the log(worth) of each parameter and removing the least important parameter first from the model.
b. Keep doing it until you are left with parameters that are significant (p-value less than 5%). Show the screenshot of Effect summary and parameter estimates and Analysis of Variance tables from JMP analysis. [5 points]
c. What is the R2 of your final model? Explain the meaning of the obtained R2. [5 points]
d. Based on the model, what is the most and least important variables in predicting the city mileage of a car? [5 points]
e. Write down the equation of the model and give an interpretation of each significant regression coefficient. [5points]

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