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Basic Probability

Mathematics, Probability and Poker

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Basic General Linear Model

The General Linear Model is y = bX + e where y is a vector valued dependent variable, X is a matrix of design elements or independent variables and e is an error vector. b is a vector of unknown coeffients.

The most basic General Linear Model is just the mean. In GML form it's written

y = b1 + e where 1 is a vector of 1's, b is the mean value.

Although we don't generally think of a mean as a General Linear Model it is a special case of one and I think it's helpful to think of the process of fitting a model as starting with the basic model, the mean.

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Alspach's Mathematics and Poker Page
Brian Alspach used to write a regular column on combinatorics for Poker Digest. He's a retired math professor from Simon Fraser University. 		Tom Ferguson's home page
He's a math ;professor at UCLA and Chris Ferguson's father. 		MathPages.com
A collection of straight-forward introductions to various topics in mathematics and recreational mathematics.

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Kelly betting

These are all somewhat technical articles.