Description: This article gives a brief overview of ways to extend clustering analysis beyond basic methods such a k-means

Description: A discussion of what to do in the face of unprecedented change. With so many negative indicators of the economic future, suggestions are made for individual actions.

Description: The author discusses expectations for incoming actuarial science students, emphasizing that a solid grasp of algebra and traditional mathematical skills is not enough. In addition, the author states that today’s business environment dictates that students be well versed and that their backgrounds include familiarity with complexity science.

Description: The author explains how he used judgmental forecasting techniques to develop a dynamic lapse assumption. He defines the techniques and provides readers with a step-by-step process.

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.