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.
Sometimes I can't remember where I put things. If I lose my glasses or garden tools, I am out of luck. But when I can't remember where I put some data, I have SAS to help me find it. When I can remember the name of the data set, my
Every year near Halloween I write a trick-and-treat article in which I demonstrate a simple programming trick that is a real treat to use. This year's trick features two of my favorite functions, the CUSUM function and the LAG function. By using these function, you can compute the rows of
The FREQ procedure in SAS supports computing exact p-values for many statistical tests. For small and mid-sized problems, the procedure runs very quickly. However, even though PROC FREQ uses efficient methods to avoid unnecessary computations, the computational time required by exact tests might be prohibitively expensive for certain tables. If
Did you know that the FREQ procedure in SAS can compute exact p-values for more than 20 statistical tests and statistics that are associated with contingency table? Mamma mia! That's a veritable smorgasbord of options! Some of the tests are specifically for one-way tables or 2 x 2 tables, but many apply
How do you simulate a contingency table that has a specified row and column sum? Last week I showed how to simulate a random 2 x 2 contingency table when the marginal frequencies are specified. This article generalizes to random r x c frequency tables (also called cross-tabulations) that have the same marginal row
A recent question posted on a discussion forum discussed storing the strictly upper-triangular portion of a correlation matrix. Suppose that you have a correlation matrix like the following: proc iml; corr = {1.0 0.6 0.5 0.4, 0.6 1.0 0.3 0.2, 0.5 0.3 1.0 0.1, 0.4 0.2 0.1 1.0}; Every correlation
When modeling and simulating data, it is important to be able to articulate the real-life statistical process that generates the data. Suppose a friend says to you, "I want to simulate two random correlated variables, X and Y." Usually this means that he wants data generated from a multivariate distribution,
This article shows how to visualize a surface in SAS. You can use the SURFACEPLOTPARM statement in the Graph Template Language (GTL) to create a surface plot. But don't worry, you don't need to know anything about GTL: just copy the code in this article and replace the names of
Suppose that you are tabulating the eye colors of students in a small class (following Friendly, 1992). Depending upon the ethnic groups of these students, you might not observe any green-eyed students. How do you put a 0 into the table that summarizes the number of students who have each
You can use SAS to generate random integers between 1–10 or in the range 1–100. This article shows how to generate random integers as easily as Excel does. I was recently talking with some SAS customers and I was asked "Why can't SAS create an easy way to generate random
