Description: The main focus of this article revolves around pension plans and their funding levels.

Description: A good primer on how clinical studies should be conducted and how statistics are used and misused to influence us.

Description: Summary of all issue articles, with theme of recognizing limits of classical actuarial methods.

Description: The July 2013 issue of the SOA’s Forecasting & Futurism section’s newsletter, Forecasting & Futurism.

Description: A book review by Scott McInturff of The Signal and the Noise: Why So Many Predictions Fail - But Some Don't authored by Nate Silver.

Description: Python & Scikit-Learn are a powerful combination for predictive modeling. Using Scikit-Learn you gain access to a variety of models, such as support vector machines, decision trees, gradient boosting and others. Scikit-Learn is very popular with the Kaggle community.

Description: This article explores a potential alternative to the more typical regression-based specification of risk adjustment models. We demonstrate a proof of concept that a nearest-neighbors approach may hold some promise in certain applications of health-based risk adjustment.

Description: Parables and Prophecies Prevent Predictive Prowess

Description: Discusses the factors one should take into account when considering the appropriate level of precision for a task or a subsequent communication.

Description: An introduction to the Forecasting & Futurism section's 2014 contest, where participants are encouraged to explore a forecasting application and develop it. The article discusses the contest, the scoring, and the prize.