I blog about a lot of topics, but the following five categories represent some of my favorite subjects. Judging by the number of readers and comments, these articles have struck a chord with SAS users. If you haven't read them, check them out. (If you HAVE read them, some are worth re-reading!)

1. SIMULATION: If you run simulations in SAS, you had better understand the four essential functions for statistical programmers. Simulation depends on random samples, so it is good to know how to generate random numbers in SAS. Lastly, it is important to understand random number streams in SAS and how they work.
2. MATRIX COMPUTATIONS: In the article "Solving linear systems: Which technique is fastest?" I show that solving a specific linear system is about four times faster than solving for a general inverse. This article also inspired the popular article, "What is the chance that a random matrix is singular?"
3. STATISTICAL PROGRAMMING: You can't program something if you don't understand it. In the article "What is Mahalanobis distance?" I describe the geometry of Mahalanobis distance, which provides a way to measure distances that takes into account correlations in the data. This article is linked to from Wikipedia because it is an "intuitive illustrated explanation." I've also written several other articles related to multivariate statistics:
4. SAS PROGRAMMING: When you run SAS 9.3 in the windowing environment, HTML is the default output destination. The article "How to clear the output window in SAS 9.3" describes how to clear the tables and graphics in the HTML destination. If you haven't yet adopted SAS 9.3, read the top five features of SAS 9.3 that every SAS user will love.
5. STATISTICAL THINKING: The internet is great for a lot of things, but not for estimating the relative popularity of topics. In the article "Estimating popularity based on Google searches: Why it's a bad idea" I argue that an estimate of popularity that is based on internet searches is a biased estimate. Statisticians at Google don't make this mistake and neither should you.
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Distinguished Researcher in Computational Statistics

Rick Wicklin, PhD, is a distinguished researcher in computational statistics at SAS and is a principal developer of SAS/IML software. His areas of expertise include computational statistics, simulation, statistical graphics, and modern methods in statistical data analysis. Rick is author of the books Statistical Programming with SAS/IML Software and Simulating Data with SAS.