Practical considerations for Predictive Modeling

Advances in computing power and in machine learning techniques are rapidly changing how humans utilize data. Aside from the core statistical issues, what are the questions that an analyst needs to consider when doing predictive modeling in practice? This post describes a few of these practical considerations. I like to use the 5 Ws to … Continue reading Practical considerations for Predictive Modeling

On being Sensitive and Specific – analytically speaking

In this (technical) post, I illustrate how to calculate commonly used goodness of fit statistics. Goodness of fit statistics are essential components to doing statistical model building. They are how you tell whether your model is performing well ito explaining the patterns in your data. In practice, most of these are done automatically from the … Continue reading On being Sensitive and Specific – analytically speaking