Does the following residual plot indicate any violation of the regression assumptions? If so, which one? Residual Select one: Predicted y values a. Zero-mean O b. Constant variance c. Independence O d. No violation
Does the following residual plot indicate any violation of the regression assumptions? If so, which one? Residual Select one: Predicted y values a. Zero-mean O b. Constant variance c. Independence O d. No violation
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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
Transcribed Image Text:**Residual Plot Analysis**
**Question:** Does the following residual plot indicate any violation of the regression assumptions? If so, which one?
**Graph Description:**
- **X-axis:** Predicted y values
- **Y-axis:** Residual
- The plot shows red dots scattered across the graph.
- There appears to be a pattern or curve in the data points rather than a random scatter.
**Options:**
- a. Zero-mean
- b. Constant variance
- c. Independence
- d. No violation
**Explanation:** The residual plot is used to diagnose violations of regression assumptions. Ideally, residuals should be randomly distributed with no discernible pattern, indicating that the model conforms to assumptions such as linearity, constant variance, and independence. If a pattern like a curve or trend is present, it may suggest a violation such as non-linearity or heteroscedasticity (violation of constant variance).
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