(Solved): WPC 300 : Lab 6: Linear Reg...

WPC 300 : Lab 6: Linear Reg

Question 1        2 pts

In a simple linear regression model that predicts home price based on the number of bedrooms, the coefficient of determination is:

Group of answer choices

• 0.44
• 0.46
• None of the given answers is correct
• 0.98

Question 2        2 pts

Is the linear model obtained in the previous question significant? Support your answer with an appropriate screenshot from JMP analysis.

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Question 3        2 pts

When you develop a prediction model for home-price, based on the beds, baths, and square feet as independent variables, which, if any, of the following independent variables is significant in the model?

Group of answer choices

• Square footage
• All of the other answers are correct
• Baths
• Beds

Question 4        2 pts

In a final model (after removing all the non-significant predictors) to predict the home price based on other variables available in the data file, the most important predictor that contributes significantly is:

Group of answer choices

• Square feet
• Acres
• Miles to base
• Baths

Question 5        2 pts

What is the model equation based on multiple regression analysis to predict home price? (reference Q4). Provide a screenshot from JMP output to show the model question.

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Question 6        2 pts

What is the coefficient of determination for the final model in previous question?

Group of answer choices

• 0.78
• 0.61
• -0.34
• 0.80

Question 7        2 pts

In the final model (reference Q4), do you have any multicollinearity issue to be addressed?

Group of answer choices

• Yes
• Need additional information such as ‘residual’ to answer this question
• No
• Need more data to answer this question

Question 8        2 pts

Share a screenshot of the appropriate table to support your answer in Q7. 

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Question 9        2 pts

Based on the final regression equation, if all variables remain the same, for an additional bath in the house, the home price wil:

Group of answer choices

• Decrease by $3.8 K
• Increase by $5.00 K
• Increase by $197 K
• Increase by $59.2 K

Question 10      2 pts

Create a frequency distribution (with summary statistics) of the residual ( Observed value - Predicted value) to show how well the model predicts the actual home price. Share the screenshot of this plot. 

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