Data on the price ($1000s) and the size (1000 ft2 sqaured) for 156 randomly selected houses that have been sold is summarized in the accompanying regression output and plots. Complete parts a and b a) Check the assumptions and conditions for inference. Select all that apply. A. The residuals look random. B. The residuals are nearly normal. C. The scatterplot looks straight enough. D. The residual plot and the scatterplot show consistent variability. E. None of the assumptions and conditions for inference are satisfied.
Data on the price ($1000s) and the size (1000 ft2 sqaured) for 156 randomly selected houses that have been sold is summarized in the accompanying regression output and plots. Complete parts a and b a) Check the assumptions and conditions for inference. Select all that apply. A. The residuals look random. B. The residuals are nearly normal. C. The scatterplot looks straight enough. D. The residual plot and the scatterplot show consistent variability. E. None of the assumptions and conditions for inference are satisfied.
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
Data on the price ($1000s) and the size (1000 ft2 sqaured) for 156 randomly selected houses that have been sold is summarized in the accompanying regression output and plots. Complete parts a and b
a) Check the assumptions and conditions for inference. Select all that apply.
The residuals look random.
The residuals are nearly normal.
The scatterplot looks straight enough.
The residual plot and the scatterplot show consistent variability.
None of the assumptions and conditions for inference are satisfied.
![Regression Output
Dependent variable is: Price
R squared = 92.2%
s = 51.05 with 156 -2 = 154 degrees of freedom
Coefficient SE(Coeff) t-ratio P-value
- 2.8680
-0.35 0.7237
180.906
8.098
4.238 42.69 ≤0.0001
Variable
Intercept
Size](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fb6fbb7bb-6654-4802-8122-921fad6cc36b%2Ff1770628-81db-4ef1-bba0-879cb5409da6%2F32muc5v_processed.png&w=3840&q=75)
Transcribed Image Text:Regression Output
Dependent variable is: Price
R squared = 92.2%
s = 51.05 with 156 -2 = 154 degrees of freedom
Coefficient SE(Coeff) t-ratio P-value
- 2.8680
-0.35 0.7237
180.906
8.098
4.238 42.69 ≤0.0001
Variable
Intercept
Size
![Price
800-
600-
400-
200-
-200-
ore 8
2 3 4 5
Size
Residuals
140-
-150+
0
Predicted
900
Count
-150
30-
Residuals
140](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fb6fbb7bb-6654-4802-8122-921fad6cc36b%2Ff1770628-81db-4ef1-bba0-879cb5409da6%2F74kfj5h_processed.png&w=3840&q=75)
Transcribed Image Text:Price
800-
600-
400-
200-
-200-
ore 8
2 3 4 5
Size
Residuals
140-
-150+
0
Predicted
900
Count
-150
30-
Residuals
140
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