Answer-first summary for fast verification
Answer: normality assumption.
## Explanation A **normal Q-Q plot** (quantile-quantile plot) is specifically used to check the **normality assumption** of regression residuals. When data points align along the diagonal line in a Q-Q plot, it indicates that the residuals follow a normal distribution. - **Linearity assumption** is typically checked using scatter plots of residuals vs. fitted values - **Independence of errors** is usually assessed using Durbin-Watson test or residual plots over time - **Homoscedasticity** (constant variance) is checked using residual plots The Q-Q plot is designed specifically for normality testing, making option B the correct answer.
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An analyst tests the assumptions of a multiple linear regression model by plotting the regression residuals on a normal Q-Q plot. If the data points align along the diagonal, this confirms the:
A
linearity assumption.
B
normality assumption.
C
independence of errors assumption.
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