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Use the following information to answer the question. Below is the scatterplot showing the association between miles driven in a semi truck (x) , and the amount of tread wear on the tires (y) . The residual plot of the data is also shown along with a QQ plot of the residuals.
Use the following information to answer the question. Below is the scatterplot showing the association between miles driven in a semi truck (x) , and the amount of tread wear on the tires (y) . The residual plot of the data is also shown along with a QQ plot of the residuals.      -Choose the statement that best describes whether the condition for normality of errors does or does not hold for the linear regression model. A) The residual plot shows no trend, therefore the normality condition is satisfied. B) The QQ plot mostly follows a straight line, therefore the normality condition is satisfied. C) The residual plot does not display a fan shape, therefore the normality condition is satisfied. D) The residual mostly follows a horizontal line which would have a slope of zero, therefore the normality condition is not satisfied. Use the following information to answer the question. Below is the scatterplot showing the association between miles driven in a semi truck (x) , and the amount of tread wear on the tires (y) . The residual plot of the data is also shown along with a QQ plot of the residuals.      -Choose the statement that best describes whether the condition for normality of errors does or does not hold for the linear regression model. A) The residual plot shows no trend, therefore the normality condition is satisfied. B) The QQ plot mostly follows a straight line, therefore the normality condition is satisfied. C) The residual plot does not display a fan shape, therefore the normality condition is satisfied. D) The residual mostly follows a horizontal line which would have a slope of zero, therefore the normality condition is not satisfied.
-Choose the statement that best describes whether the condition for normality of errors does or does not hold for the linear regression model.


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