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The following data was collected to explore how the number of square feet in a house, the number of bedrooms, and the age of the the selling price of the house. The dependent variable is the selling price of the house, the first independent variable (x₁) is the square footage, the second independent variable (x₂) is the number of bedrooms, and the third independent variable (x)) is the age of the house. Square Feet 2786 1632 3054 2332 2223 1661 1326 2909 1793 Effects on Selling Price of Houses Number of Bedrooms Age 5 6 3 7 3 7 3 2 4 13 2 1 4 2 2 10 3 2 Selling Price 274400 137900 116200 159600 135400 201900 170000 182800 217100 Step 1 of 2: Find the p-value for the regression equation that fits the given data. Round your answer to four decimal places. Copy Data

The following data was collected to explore how the number of square feet in a house, the number of bedrooms, and the age of the the selling price of the house. The dependent variable is the selling price of the house, the first independent variable (x₁) is the square footage, the second independent variable (x₂) is the number of bedrooms, and the third independent variable (x)) is the age of the house. Square Feet 2786 1632 3054 2332 2223 1661 1326 2909 1793 Effects on Selling Price of Houses Number of Bedrooms Age 5 6 3 7 3 7 3 2 4 13 2 1 4 2 2 10 3 2 Selling Price 274400 137900 116200 159600 135400 201900 170000 182800 217100 Step 1 of 2: Find the p-value for the regression equation that fits the given data. Round your answer to four decimal places. Copy Data

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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The following data was collected to explore how the number of square feet in a house, the number of bedrooms, and the age of the house affect the selling price of the house. The dependent variable is the selling price of the house, the first independent variable (x₁) is the square footage, the second independent variable (x₂) is the number of bedrooms, and the third independent variable (x) is the age of the house. Square Feet 2786 1632 3054 2332 2223 1661 1326 2909 1793 Effects on Selling Price of Houses Number of Bedrooms Age 5 6 3 7 3 7 3 2 4 13 2 1 4 2 2 10 3 2 Selling Price 274400 137900 116200 159600 135400 201900 170000 182800 217100 Step 1 of 2: Find the p-value for the regression equation that fits the given data. Round your answer to four decimal places.. Copy Data N
Transcribed Image Text:The following data was collected to explore how the number of square feet in a house, the number of bedrooms, and the age of the house affect the selling price of the house. The dependent variable is the selling price of the house, the first independent variable (x₁) is the square footage, the second independent variable (x₂) is the number of bedrooms, and the third independent variable (x) is the age of the house. Square Feet 2786 1632 3054 2332 2223 1661 1326 2909 1793 Effects on Selling Price of Houses Number of Bedrooms Age 5 6 3 7 3 7 3 2 4 13 2 1 4 2 2 10 3 2 Selling Price 274400 137900 116200 159600 135400 201900 170000 182800 217100 Step 1 of 2: Find the p-value for the regression equation that fits the given data. Round your answer to four decimal places.. Copy Data N
Step 2 of 2: Determine if a statistically significant linear relationship exists between the independent and dependent variables at the 0.01 level of significance. If the relationship is statistically significant, identify the multiple regression equation that best fits the data, rounding the answers to three decimal places. Otherwise, indicate that there is not enough evidence to show that the relationship is statistically significant.
Transcribed Image Text:Step 2 of 2: Determine if a statistically significant linear relationship exists between the independent and dependent variables at the 0.01 level of significance. If the relationship is statistically significant, identify the multiple regression equation that best fits the data, rounding the answers to three decimal places. Otherwise, indicate that there is not enough evidence to show that the relationship is statistically significant.
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