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Rick Wicklin
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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.

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An improved simulation of card shuffling

Last week I presented the GSR algorithm, a statistical model of a riffle shuffle. In the model, a deck of n cards is split into two parts according to the binomial distribution. Each piece has roughly n/2 cards. Then cards are dropped from the two stacks according to the number

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Funnel plots: An alternative to ranking

In a previous blog post, I showed how you can use simulation to construct confidence intervals for ranks. This idea (from a paper by E. Marshall and D. Spiegelhalter), enables you to display a graph that compares the performance of several institutions, where "institutions" can mean schools, companies, airlines, or

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A statistical model of card shuffling

I recently returned from a five-day conference in Las Vegas. On the way there, I finally had time to read a classic statistical paper: Bayer and Diaconis (1992) describes how many shuffles are needed to randomize a deck of cards. Their famous result that it takes seven shuffles to randomize

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The sound of the Dow...in SAS

At the beginning of 2011, I heard about the Dow Piano, which was created by CNNMoney.com. The Dow Piano visualizes the performance of the Dow Jones industrial average in 2010 with a line plot, but also adds an auditory component. As Bård Edlund, Art Director at CNNMoney.com, said, The daily

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Computing the variance of each column of a matrix

In a previous blog post about computing confidence intervals for rankings, I inadvertently used the VAR function in SAS/IML 9.22, without providing equivalent functionality for those readers who are running an earlier version of SAS/IML software. (Thanks to Eric for pointing this out.) If you are using a version of

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How to rank values

When comparing scores from different subjects, it is often useful to rank the subjects. A rank is the order of a subject when the associated score is listed in ascending order. I've written a few articles about the importance of including confidence intervals when you display rankings, but I haven't

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How to sample from independent normal distributions

In my article on computing confidence intervals for rankings, I had to generate p random vectors that each contained N random numbers. Each vector was generated from normal distribution with different parameters. This post compares two different ways to generate p vectors that are sampled from independent normal distributions. Sampling

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