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Can anyone explain why the BP, Breusch-Pagan, test rejects homoscedasticity with such an apparently randomized plot of residuals?

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Info5ek
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You have drawn the wrong scatterplot, I believe.

You should have a scatterplot of the residuals against the fitted values from the model, not "index" which is just the order in which the observations went into the data set

Peter Flom
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  • I used plot(resid(lm(x)))

    I'm confused because I thought the point of looking at residuals was to ensure that they are evenly scattered about the line Y = 0.

     – Info5ek Mar 16 '14 at 22:18
  • No. That is true by force. The point is to see if the residuals violate the assumptions of OLS regression: 1) Normally distributed 2) Not related to the fitted values 3) Constant variance at different levels. Try plot(m1) in R, where m1 is a linear model; this gives a good default set of graphs – Peter Flom Mar 16 '14 at 22:21
  • i replaced the initial plot with he residuals vs fitted plot – Info5ek Mar 16 '14 at 22:27
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    @user1800340, you don't want the residuals vs fitted. This plot tells you there is some curvature in the x y relationship that isn't being captured by your model. To assess homoscedasticity, you want to call plot(model, which=2), which will give you scale-location plot (see my answer here). – gung - Reinstate Monica Mar 16 '14 at 22:58