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WPC 300 Assignment 7 1

 

WPC 300 (Hybrid Course)

Assignment-7

Maximum points: 25

                           

Student Name:  _[Mary Alfansha ]___________________ Class Day & Time:__[Monday & 9.15 AM]_

 

 

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]

 

  1. 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]

 

  1. 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]

 

  1. Based on the model, what are the most and least important variables in predicting the city mileage of a car? [5 points]

 

  1. Write down the equation of the regression model and give an interpretation of each significant coefficient of the model. [5points]

 

 



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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]

WPC 300 Assignment 7 2

  1. 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.

 

After removing several insignificant parameters

WPC 300 Assignment 7

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

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