Question

In a regression analysis, what assumption can be checked with a normal probability plot of the residuals, and what should one look for in such a plot?

(A) x and y are correlated. Look for a straight line pattern. (B) The residuals all have the same variance. Look for a straight line pattern. The vertical variation in the plot should be roughly constant throughout the whole range of fitted values. (C) The residuals follow a normal distribution. Look for a straight line pattern. (D) The residuals follow a normal distribution. Look for a random scattering of points, with no patterns in the plot. The vertical variation in the plot should be roughly constant throughout the whole range of fitted values. (E) The residuals all have the same variance. Look for a straight line pattern. F) The residuals all have the same variance. Look for a random scattering of points, with no patterns in the plot. The vertical variation in the plot should be roughly constant throughout the whole range of fitted values. (G) The residuals follow a normal distribution. Look for a bell shape. (H) y is linearly related to at least one of the x variables. Look for a bell shape

Answer 1

Well, if the line is a good fit for the data then the residual plot will be random. However, if the line is a bad fit for the data then the plot of the residuals will have a pattern.

The residuals all have the same variance. Look for a random scattering of points,
with no patterns in the plot. The vertical variation in the plot should be roughly constant
throughout the whole range of fitted values.

Option F is correct.

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