Ever wonder what sorts of errors freshman math students make? There are a couple of pretty basic ones.

The linear response function, which could also be specified as RESPONSE MARGINALS, yields one probability, Pr (brand preference=M), as the response function to be analyzed.

You construct a generalized linear model by deciding on response and explanatory variables for your data and choosing an appropriate link function and response probability distribution. Some examples ...

In some overparameterized linear models it can be difficult to determine which parametric functions are estimable. Students in linear models courses and data analysts ...