http://www.jiem.org/index.php/jiem/article/viewFile/60/27

Probably that’s why logistic function is used to model the probability of a binary event (derived from utility point of view)

Also an intuitive post: http://www.johndcook.com/blog/2010/05/18/normal-approximation-to-logistic/

The shape of logistic function looks like the CDF of normal distribution.

As pointed out by Poole et al, the error term of the utility function may follow **logit**, **Weibull**, or **normal** **distribution**.

We may get prob = logis(xa+b) if error ~ logit distribution.