Errors in Statistical Modeling

(or why keep the human in the loop)

Statistical Models’ accuracy depends as much on the information left out of them, if not more, as on the information included in them. In this post, I discuss two main concepts of errors: reducible and irreducible, and why domain knowledge and subject matter experts are key to maximizing model accuracy.

Let’s say you wish to understand the factors influencing sales in an organization so as to …

data science mathematics modeling predictions statistical statistical-learning statistical modeling uncertainty