As an example, consider the
ChickWeight data set in R. The variance obviously grows over time, so if I use a simple linear regression like:
m <- lm(weight ~ Time*Diet, data=ChickWeight)
which aspects of the model will be questionable? Are the problems limited to extrapolating outside the Time range? How tolerant is linear regression to violation of this assumption (i.e., how heteroscedastic does it have to be to cause problems?).