Answered: Step 2 of 2: Determine if a… | bartleby

MATLAB: An Introduction with Applications

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Question

The table titled "Effects on Selling Price of Houses" displays data on several factors influencing house prices. Each row represents a different house with the following columns:

- **Square Feet**: The total square footage of the house.
- **Number of Bedrooms**: The number of bedrooms in the property.
- **Age**: The age of the house in years.
- **Selling Price**: The selling price of the house in dollars.

Here is the data in the table:

| Square Feet | Number of Bedrooms | Age | Selling Price |
|-------------|---------------------|-----|---------------|
| 2683 | 3 | 2 | 107,100 |
| 1889 | 4 | 2 | 212,400 |
| 2602 | 4 | 8 | 293,400 |
| 1905 | 3 | 5 | 202,200 |
| 2851 | 4 | 6 | 115,400 |
| 1916 | 5 | 14 | 304,600 |
| 1920 | 2 | 7 | 153,900 |
| 1634 | 3 | 8 | 263,500 |
| 1258 | 4 | 13 | 189,500 |

**Step 2 of 2**: This section discusses determining if there is a statistically significant linear relationship between the independent variables (square feet, number of bedrooms, and age) and the dependent variable (selling price) at a 0.05 level of significance.

- If the relationship is statistically significant, the task is to find the multiple regression equation that best fits the data, rounded to three decimal places.
- If not, it should be indicated that there is not enough evidence to show a statistically significant relationship.

There is a section provided to fill out the possible regression equation:
\[ \hat{y} = \text{(intercept)} + \text{(coefficient for square feet)} \times x_1 + \text{(coefficient for bedrooms)} \times x_2 + \text{(coefficient for age)} \times x_3 \]

There is also a checkbox option stating "There is not enough evidence" if the relationship is not significant.

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