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

In this problem, the optimal path is one that maximizes the expected utility, with the utility function being piecewise-linear and concave. Such a utility function can be used to approximate nonlinear ...

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 ...

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.

We demonstrate the implementation of a variety of non-linear models that are more appropriate for modeling plant growth than are the traditional, linear, models.Ecological inference is frequently ...

Generalized linear models are widely used by data analysts. However, the choice of the link function is often made arbitrarily. Here we permit the data to estimate the link function by incorporating ...

It only makes sense. I did linear regression in google docs and I did it for python. But what if you neither of those? Can you do it by hand? Why yes. Suppose I take the same data from the pylab ...