9 Off-the-beaten-path Statistical Science Topics with Interesting Applications

You will find here nine interesting topics that you won't learn in college classes. Most have interesting applications in business and elsewhere. They are not especially difficult, and I explain them in simple English. Yet they are not part of the traditional statistical curriculum, and even many data scientists with a PhD degree have not heard about some of these concepts.

The topics discussed in this article include:

• Random walks in one, two and three dimensions - With Video
• Estimation of the convex hull of a set of points - Application to clustering and oil industry
• Constrained linear regression on unusual domains - Application to food industry
• Robust and scale-invariant variances
• Distribution of arrival times of extreme events - Application to flood predictions
• The Tweedie distributions - Numerous applications
• The arithmetic-geometric mean - Fast computations of decimals of Pi
• Weighted version of the K-NN clustering algorithm
• Multivariate exponential distribution and storm modeling

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