Hi Becky-
When looking for nonnormality of the disturbances, we want to look at the
distribution of the studentized residuals (this is what the qq.plot
function does). Viewing a histogram of the residuals (and, at times, the
y values, if we think skewed y values may be inducing nonnormality in the
residuals) can help us identify multimodality in the residuals.
There is generally no need to look at the distribution of our individual
x variables, though. You might look to Fox's example analysis p. 298-299.
good luck-
Alison
On Sun, 5 Dec 2004, Rebecca Marie Nelson wrote:
Hi Alison,
I was looking at histogram plots of the x variables..... are we just
concerned with the Y variable in non-normality of disturbances?
Becky
On Sun, 5 Dec 2004, Alison Elizabeth Post wrote:
Becky-
I'm a little confused about how you're going about this.
Generally, we generate a qq.plot of the residuals from the lm output:
qq.plot(lm.out)
So this tells us about the distribution of the residuals generally. It
does not relate the distribution of these residuals to a particular
explanatory variable like pop15. Are you instead plotting particular x
variables using the qq.plot function?
A
On Sun, 5 Dec 2004, Rebecca Marie Nelson wrote:
Hi,
When correcting for non-normailty of disturbances, I understand how to
correct for skewness. I do not understand how to correct for
multi-modality, which it looks like pop15 has. Are we supposed to correct
for this problem this week or just recognize that it is a problem and we
will correct for it later?
Thanks,
Becky
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