As far as I can tell, generalized linear models are the same as
general linear regression except that the error term is generalized to
be other than normally distributed.  If that's all it is, why did it
take so long before it got the same treatment as linear regression? 
What makes the subject any more complex than linear regression?  Do
error terms' being normal really help simplify the analysis so much? 
Thank you in
advance.