The General Linear Model Is Not Maximally General

The general linear model is a special case of the general lized linear model. The link n on takes us from that beautiful s curve, linearizes it where we fit our linear predictors and then we can back out of it to get back to what r our probability and odds are. Can we predict the probability of a figol kicker making a kick as a function of how far away they are from the uprights? Statistically, the most accurate kicker in nfl history. Look at that stair. He's in disbelief. And i kind of like that because the randomp et is the response distribution,. How are you introducing variability into the mall? Well, add this to the list