# (Solved): WPC 300 : Lab 6: Linear Reg 2021...

**WPC300 **

**Lab 6: Linear Reg**

**Quiz Instructions**

- Start with datafile:
- Change the file names to: YourFirstName_YourLastName_housingprices.jmp
- Review what we did in the lab.
- You must use JMP to answer the following multiple-choice questions.
**Note: When you are asked to submit a screen capture, you need to make sure that your name is part of the capture.**

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

None of the given answers is correct

0.44

0.98

0.46

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

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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

All of the other answers are correct

Square footage

Baths

Beds

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
- Baths
- Miles to base

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

Group of answer choices

- 0.61
- 0.78
- -0.34
- 0.80

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

Group of answer choices

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

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

- Increase by $197 K
- Increase by $59.2 K
- Decrease by $3.8 K
- Increase by $5.00 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.