Statistics and Behavioral Modeling

Intriguing article, by Steve Miller. I have now dealt with these 'two cultures' a number of times in various enterprises. This article and the included link are worth the read ... about the application of traditional statistics in behavioral realms ...

' ... My take on the article was less literal. I think the author's point that traditional statistical models might not be up to the task of predicting the realities of human behavior is quite valid. In fact, one of the giants of the statistical world, the late UC Berkeley professor Leo Breiman, originator of Classification and Regression Trees (CART) and Random Forests, said as much in a provocative 2001 article, Statistical Modeling: The Two Cultures, in which he criticized the statistics status quo. The abstract for this paper is telling:

"There are two cultures in the use of statistical modeling to reach conclusions from data. One assumes that the data are generated by a given stochastic data model. The other uses algorithmic models and treats the data mechanism as unknown. The statistical community has been committed to the almost exclusive use of data models. This commitment has led to irrelevant theory, questionable conclusions, and has kept statisticians from working on a large range of interesting current problems. Algorithmic modeling, both in theory and practice, has developed rapidly in fields outside statistics. It can be used both on large complex data sets and as a more accurate and informative alternative to data modeling on smaller data sets. If our goal as a field is to use data to solve problems, then we need to move away from exclusive dependence on data models and adopt a more diverse set of tools.” ... '