Well how about I flip it back to you and say what if there is a pattern in the error, say they are shaped like a funnel? So they are very small and get larger and larger as the x variable increases.
I have been reading up on linear regression and residual plots here on stattrek:
http://stattrek.com/regression/resid...px?Tutorial=AP
The page contains the following:
"A residual plot is a graph that shows the residuals on the vertical axis and the independent variable on the horizontal axis. If the points in a residual plot are randomly dispersed around the horizontal axis, a linear regression model is appropriate for the data; otherwise, a non-linear model is more appropriate."
I cant figure out why randomly dispersed points suggest a linear regression model is appropriate; and dispersped points in an ordered manner being inappropriate.
Can anyone elaborate, in layman terms, why this is the case??
Many thanks in advance
Well how about I flip it back to you and say what if there is a pattern in the error, say they are shaped like a funnel? So they are very small and get larger and larger as the x variable increases.
Stop cowardice, ban guns!
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