Dating database schema
However, statistics is probably a much friendlier branch of mathematics because it really can be used every day.
Statistics was in fact born from very humble beginnings of real world problems from business, biology, and gambling!
Excerpted from the book Building Data Mining Applications for CRM by Alex Berson, Stephen Smith, and Kurt Thearling This overview provides a description of some of the most common data mining algorithms in use today.
We have broken the discussion into two sections, each with a specific theme: Each section will describe a number of data mining algorithms at a high level, focusing on the "big picture" so that the reader will be able to understand how each algorithm fits into the landscape of data mining techniques.
Some of the techniques that are classified under data mining such as CHAID and CART really grew out of the statistical profession more than anywhere else, and the basic ideas of probability, independence and causality and overfitting are the foundation on which both data mining and statistics are built.
One thing that is always true about statistics is that there is always data involved, and usually enough data so that the average person cannot keep track of all the data in their heads.
Thus this section contains descriptions of techniques that have classically been used for decades the next section represents techniques that have only been widely used since the early 1980s.The bottom line though, from an academic standpoint at least, is that there is little practical difference between a statistical technique and a classical data mining technique.